Artículos de revistas: "Smarty (Computer file)"

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Alrobieh, Ziad Saif y Ali Mohammed Abdullah Ali Raqpan. "File Carving Survey on Techniques, Tools and Areas of Use". Transactions on Networks and Communications 8, n.º 1 (28 de febrero de 2020): 16–26. http://dx.doi.org/10.14738/tnc.81.7636.

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In digital and computer forensics, file carving is a very hot research topic. That is the main reason why the research is needed to be focused on improving file carving techniques, so that digital investigation can obtain important data and evidence from damaged or corrupted storage media. In the digital forensic investigation, analyzing the unallocated space of storage media is necessary to extract the deleted or pre-written files when the file system metadata is missing or corrupted. Data carving can be defined as a method to recover the file from unallocated space based on different factors such as file type, information of the file (Header/Footer), or the contents of the file. Research in this area focuses on technological improvements in terms of tools and techniques over the past years. The studies examine different techniques of data carving, especially multimedia files (eg. images and videos). The work file carving is classified into three categories classic carving techniques, intelligent carving techniques and smart carving techniques. Moreover, there are seven popular multimedia carving tools that are mostly used and experimentally evaluated are presented. We conclude that proposing new advanced method for carving multimedia files still open and new direction for future research. This is because the fragmentations and compression are very commons used and useful for these kind of files.

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Harabuga, Yu S. "FEATURES OF COMPUTER TECHNICAL RESEARCH OF THE INFORMATION IN THE MEMORY OF SIM, USIM AND R-UIM-CARDS". Theory and Practice of Forensic Science and Criminalistics 17 (29 de noviembre de 2017): 318–24. http://dx.doi.org/10.32353/khrife.2017.40.

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The paper considers the features of expert research of elementary files contents of SIM, USIM and R-UIM-cards, the information on which is absent in the current edition of technique 10.9.10 «Technique of computer technical research of information in the memory of SIM-cards». Effective standards which regulate the structure of files in SIM, USIM and R-UIM-cards, are specified. For today there are three types of identification modules of cellular communication customers: SIM-cards for networks of standard GSM, R-UIM-cards for networks ofstandard CDMA and USIM-cards for networks ofstandards UMTS and LTE. The hierarchical structure of a SIM-card corresponds to the hierarchical structure of a smart card of standard ISO/IEC 7816-4 and consists from three types of files: the main file (MF), the intended file (DF) and an elementary file (EF). For addressing or identification of each concrete file the identifier of a file is used which consists of two bytes. The first byte ofthe identifier definesfile type. The attention is paid to the elementary file EFspn in which the name of a cellular communication operator is stored. The theoretical and practical information concerning research of the content of the intended file DFpHONEBCOK is presented in which the telephone book of an USIM-card is stored. It’s specified that elementary file EFSMS is stored in the memory of a R-UIM-card in other intended file in comparison with SIM and USIM-cards. The research algorithm of contents EFSMS file in memory of a R-UIM-card is offered. The attention that in identification number of a R-UIM-card some Ukrainian CDMA-operators specify a mobile code of the country 255 instead of the international telephone code of Ukraine 380, is paid. Keeping in mind the presented information will help to avoid expert errors during computer technical research of the information in the memory of SIM, USIM and R-UIM-cards.

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N. Sangeeta y Seung Yeob Nam. "Blockchain and Interplanetary File System (IPFS)-Based Data Storage System for Vehicular Networks with Keyword Search Capability". Electronics 12, n.º 7 (24 de marzo de 2023): 1545. http://dx.doi.org/10.3390/electronics12071545.

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Closed-circuit television (CCTV) cameras and black boxes are indispensable for road safety and accident management. Visible highway surveillance cameras can promote safe driving habits while discouraging moving violations. According to CCTV laws, footage captured by roadside cameras must be securely stored, and authorized persons can access it. Footages collected by CCTV and Blackbox are usually saved to the camera’s microSD card, the cloud, or hard drives locally but there are concerns about security and data integrity. These issues may be addressed by blockchain technology. The cost of storing data on the blockchain, on the other hand, is prohibitively expensive. We can have decentralized and cost-effective storage with the interplanetary file system (IPFS) project. It is a file-sharing protocol that stores and distributes data in a distributed file system. We propose a decentralized IPFS and blockchain-based application for distributed file storage. It is possible to upload various types of files into our decentralized application (DApp), and hashes of the uploaded files are permanently saved on the Ethereum blockchain with the help of smart contracts. Because it cannot be removed, it is immutable. By clicking on the file description, we can also view the file. DApp also includes a keyword search feature to assist us in quickly locating sensitive information. We used Ethers.js’ smart contract event listener and contract.queryFilter to filter and read data from the blockchain. The smart contract events are then written to a text file for our DApp’s keyword search functionality. Our experiment demonstrates that our DApp is resilient to system failure while preserving the transparency and integrity of data due to the immutability of blockchain.

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Carthen, Chase D., Araam Zaremehrjardi, Vinh Le, Carlos Cardillo, Scotty Strachan, Alireza Tavakkoli, Frederick C. Harris Jr. y Sergiu M. Dascalu. "A Novel Spatial Data Pipeline for Orchestrating Apache NiFi/MiNiFi". International Journal of Software Innovation 12, n.º 1 (1 de noviembre de 2023): 1–14. http://dx.doi.org/10.4018/ijsi.333164.

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In many smart city projects, a common choice to capture spatial information is the inclusion of lidar data, but this decision will often invoke severe growing pains within the existing infrastructure. In this article, the authors introduce a data pipeline that orchestrates Apache NiFi (NiFi), Apache MiNiFi (MiNiFi), and several other tools as an automated solution to relay and archive lidar data captured by deployed edge devices. The lidar sensors utilized within this workflow are Velodyne Ultra Puck sensors that produce 6-7 GB packet capture (PCAP) files per hour. By both compressing the file after capturing it and compressing the file in real-time; it was discovered that GZIP and XZ both saved considerable file size being from 2-5 GB, 5 minutes in transmission time, and considerable CPU time. To evaluate the capabilities of the system design, the features of this data pipeline were compared against existing third-party services, Globus and RSync.

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Telagam, Nagarjuna, Nehru Kandasamy, Menakadevi Nanjundan y Arulanandth TS. "Smart Sensor Network based Industrial Parameters Monitoring in IOT Environment using Virtual Instrumentation Server". International Journal of Online Engineering (iJOE) 13, n.º 11 (22 de noviembre de 2017): 111. http://dx.doi.org/10.3991/ijoe.v13i11.7630.

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A remote monitoring and control are one of the most important criteria for maximizing the production in any industry. With the development of modern industry the requirement for industrial monitoring system is getting higher. This project explains the real time scenario of monitoring temperature and humidity in industries. National Instruments my RIO is used and results are observed on Lab VIEW and VI Server. The server VI program and client VI program is developed in block diagram for the two sensor data. This proposed system develops a sensor interface device essential for sensor data acquisition of industrial Wireless Sensor Networks (WSN) in Internet of Things (IOT) environment. By detecting the values of sensors like temperature, humidity present in the industrial area. The results are displayed on the web page. The data can be accessed with admin name and password. After logging into the web page the index of files is displayed. After restarting the mine RIO kit and initiate the deploying process the nations will display log.csv file. By double clicking the file the excel sheet will appear on the computer. This VI server is tested for its working, using a data acquisition web application using a standard web browser. The critical situation can be avoided and preventive measures are successfully implemented.

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Alukwe, Chrispus. "Enhancing Cybersecurity: Smart Intrusion Detection in File Server SYSTEMS". Journal of Science, Innovation and Creativity 2, n.º 1 (17 de agosto de 2023): 1–6. http://dx.doi.org/10.58721/jsic.v2i1.287.

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System security is a major challenge worldwide, which has led to the increasing implementation of security surveillance systems in the public and private sectors. Likewise, it is inevitable to secure server-based systems that store vast amounts of sensitive data that is accessed from time to time. Intrusion Detection Systems (IDS) use metrics to detect anomalous activity on computers and computer networks. Modern detection algorithms try to reach detection metrics by acting as an antivirus. This is not enough, the need to explore more controlled, porous, and more secure systems is inevitable, hence this research. Therefore, this study’s main objective is to develop smart intrusion detection systems for file servers and client machines that can be used within any networked environment. A qualitative research methodology was employed in the study. The sources of information included four databases: SpringerOpen, EBSCO, Google Scholar, and Direct Science. The key findings of the study are that cyber-attacks and threats are increasing, and new strategies are needed to handle them because the current intrusion detection systems experience challenges and are unable to detect malware. Intrusion detection systems are the next-generation protection, which offers the visibility to identify advanced threats within legitimate content, even authorized applications and trusted sources. Organizations are recommended to implement smart IDSs in front of file server systems and behind the firewall to ensure all malware is filtered.

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Srivastava, Nayan. "A.I.- Smart Assistant". International Journal for Research in Applied Science and Engineering Technology 9, n.º VI (25 de junio de 2021): 2384–87. http://dx.doi.org/10.22214/ijraset.2021.35553.

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Artificial Intelligent is widely used when it comes to everyday life. Computer science explains AI research as a study of brilliant agents. Every In almost any direction one turns to today, some computer-based information processing technology intervention, whether by a person knowingly or not. Artificial Intelligence has already changed our way of life. A device that we can see in its nature and take action increases its chances of success goals. Input to the recommendations algorithm can be a file for user database and items, and careless removal will be recommendations. User to install in the system by voice or text. This paper presents a new approach to it. All over the world, many people use the assistant. This paper introduces visual applications an assistant that helps to give humanity a chance at various domains. This paper also describes the annoyance of using visual assistant technology.

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Qiao, Yanchen, Weizhe Zhang, Xiaojiang Du y Mohsen Guizani. "Malware Classification Based on Multilayer Perception and Word2Vec for IoT Security". ACM Transactions on Internet Technology 22, n.º 1 (28 de febrero de 2022): 1–22. http://dx.doi.org/10.1145/3436751.

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With the construction of smart cities, the number of Internet of Things (IoT) devices is growing rapidly, leading to an explosive growth of malware designed for IoT devices. These malware pose a serious threat to the security of IoT devices. The traditional malware classification methods mainly rely on feature engineering. To improve accuracy, a large number of different types of features will be extracted from malware files in these methods. That brings a high complexity to the classification. To solve these issues, a malware classification method based on Word2Vec and Multilayer Perception (MLP) is proposed in this article. First, for one malware sample, Word2Vec is used to calculate a word vector for all bytes of the binary file and all instructions in the assembly file. Second, we combine these vectors into a 256x256x2-dimensional matrix. Finally, we designed a deep learning network structure based on MLP to train the model. Then the model is used to classify the testing samples. The experimental results prove that the method has a high accuracy of 99.54%.

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Chen, Zhenwei, Axin Wu, Yifei Li, Qixuan Xing y Shengling Geng. "Blockchain-Enabled Public Key Encryption with Multi-Keyword Search in Cloud Computing". Security and Communication Networks 2021 (20 de enero de 2021): 1–11. http://dx.doi.org/10.1155/2021/6619689.

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The emergence of the cloud storage has brought great convenience to people’s life. Many individuals and enterprises have delivered a large amount of data to the third-party server for storage. Thus, the privacy protection of data retrieved by the user needs to be guaranteed. Searchable encryption technology for the cloud environment is adopted to ensure that the user information is secure with retrieving data. However, most schemes only support single-keyword search and do not support file updates, which limit the flexibility of the scheme. To eliminate these problems, we propose a blockchain-enabled public key encryption scheme with multi-keyword search (BPKEMS), and our scheme supports file updates. In addition, smart contract is used to ensure the fairness of transactions between data owner and user without introducing a third party. At the data storage stage, our scheme realizes the verifiability by numbering the files, which ensures that the ciphertext received by the user is complete. In terms of security and performance, our scheme is secure against inside keyword guessing attacks (KGAs) and has better computation overhead than other related schemes.

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Jawdhari, Hayder A. y Alharith A. Abdullah. "A New Environment of Blockchain based Multi Encryption Data Transferring". Webology 18, n.º 2 (30 de diciembre de 2021): 1379–91. http://dx.doi.org/10.14704/web/v18i2/web18396.

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Blockchain is one of the technologies provided by the global distribution of computing power. Simply put, the blockchain is the digital ledger in which transactions are recorded. It all started with a desire to see a new form of security system for transferring confidential files. It aims to achieve many goals like decreasing the process time for transferring files to the other party, and reducing the overall expenses as the files are only transferred across the blockchain network with no need for the files to be uploaded and downloaded to the drive. More effective applications have the ability to share files via the technology of Blockchain. The great challenge is to build a private blockchain environment to send files and distribute them securely between parties, such as military institutions and others. In this paper, a private blockchain is built to overcome the side of the security through a secured file-sharing network. This private Blockchain can be utilized at various institutions. A high scale of security is obtained through using an important algorithm that takes into consideration a critical part of the field of cryptography to robustly encrypt the files. The latter ensures that no individual except for the receiver has the ability to access the files. As well, a sufficient speed was obtained when transferring the files, as compared to Ethereum with FTP. Finally, smart contracts have been designed to suit the transfer of files between nodes.

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Prat, Lionel, Cheryl Baker y Nhien An Le-Khac. "MapExif". International Journal of Digital Crime and Forensics 7, n.º 2 (abril de 2015): 53–78. http://dx.doi.org/10.4018/ijdcf.2015040104.

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Recently, the integration of geographical coordinates into a picture has become more and more popular. Indeed almost all smartphones and many cameras today have a built-in GPS receiver that stores the location information in the Exif header when a picture is taken. Although the automatic embedding of geotags in pictures is often ignored by smart phone users as it can lead to endless discussions about privacy implications, these geotags could be really useful for investigators in analysing criminal activity. Currently, there are many free tools as well as commercial tools available in the market that can help computer forensics investigators to cover a wide range of geographic information related to criminal scenes or activities. However, there are not specific forensic tools available to deal with the geolocation of pictures taken by smart phones or cameras. In this paper, an image scanning and mapping tool for investigators is proposed and developed. This tool scans all the files in a given directory and then displays particular photos based on optional filters (date/time/device/localisation…) on Google Map. The file scanning process is not based on the file extension but its header. This tool can also show efficiently to users if there is more than one image on the map with the same GPS coordinates, or even if there are images with no GPS coordinates taken by the same device in the same timeline. Moreover, this new tool is portable; investigators can run it on any operating system without any installation. Another useful feature is to be able to work in a read-only environment, so that forensic results will not be modified. This tool's real-world application is also presented and evaluated in this paper.

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Lee, Jino y Taeshik Shon. "Forensic Analysis of IoT File Systems for Linux-Compatible Platforms". Electronics 11, n.º 19 (8 de octubre de 2022): 3219. http://dx.doi.org/10.3390/electronics11193219.

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Due to recent developments in IT technology, various IoT devices have been developed for use in various environments, such as card smart TVs, and smartphones Communication between IoT devices has become possible. Various IoT devices are found in homes and in daily life, and IoT technologies are being combined with vehicles, power, and wearables, amongst others. Although the usage of IoT devices has increased, the level of security technology applied to IoT devices is still insufficient. There is sensitive information stored inside IoT devices, such as personal information and usage history, so if security accidents happen, such as data leakage, it can be very damaging for users. Since research on data storage and acquisition in IoT devices is very important, in this paper we conducted a security analysis, from a forensic perspective, on IoT platform file systems used in various environments. The analysis was conducted on two mechanical platforms: Tizen (VDFS) and Linux (JFFS2 and UBIFS). Through file system metadata analysis, file system type, size, list of files and folders, deleted file information were obtained so that we could analyze file system structure with the obtained information. We also used the obtained information to check the recoverability of deleted data to investigate the recovery plan. In this study, we explain the characteristics of platforms used in various environments, and the characteristics of data stored in each platform. By analyzing the security issues of data stored during platform communications, we aimed to help in solving the problems affecting devices. In addition, we explain the analysis method for file system forensics so that it can be referred to in other platform forensics.

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Hammad, Muhammad, Jawaid Iqbal, Ch Anwar ul Hassan, Saddam Hussain, Syed Sajid Ullah, Mueen Uddin, Urooj Ali Malik, Maha Abdelhaq y Raed Alsaqour. "Blockchain-Based Decentralized Architecture for Software Version Control". Applied Sciences 13, n.º 5 (27 de febrero de 2023): 3066. http://dx.doi.org/10.3390/app13053066.

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Version control is an important component of configuration management, and most enterprise-level software uses different tools and technologies to manage the software version control such as CVS, Subversion, or Perforce. Following the success of bitcoin, the first practical application of blockchain, it is being implemented in other fields such as healthcare, supply chains, financial management, real estate, electoral systems, and so on. Blockchain’s core features include decentralization, immutability, and interminability. Most version control repositories are centralized and can be modified by external sources, implying that they are in danger of being corrupted or controlled. In this study, we present the BDA-SCV architecture for implementing a version control system in blockchain technology. Our proposed approach would replace the necessity for a centralized system, with a decentralized approach implemented in the blockchain using distributed file storage, for which we will use the InterPlanetary File System (IPFS), which is a distributed file system. The proof of authority (PoA) consensus algorithm will be used to approve the developer communicating modifications to the private blockchain network; the authority will only provide permission and will not be able to add, edit, or delete code files. For each change, a ledger block will be created with a reference to the file stored in the distributed repository. A block cannot be manipulated once it has been created. Smart contracts will be used to register developers, create blocks, and manage the repository. The suggested model is implemented using the Hyperledger Fabric network, and the developer and authorizer ends are built into the dotnet web application.

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Ai, Sophy y Jangwoo Kwon. "Extreme Low-Light Image Enhancement for Surveillance Cameras Using Attention U-Net". Sensors 20, n.º 2 (15 de enero de 2020): 495. http://dx.doi.org/10.3390/s20020495.

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Low-light image enhancement is one of the most challenging tasks in computer vision, and it is actively researched and used to solve various problems. Most of the time, image processing achieves significant performance under normal lighting conditions. However, under low-light conditions, an image turns out to be noisy and dark, which makes subsequent computer vision tasks difficult. To make buried details more visible, and reduce blur and noise in a low-light captured image, a low-light image enhancement task is necessary. A lot of research has been applied to many different techniques. However, most of these approaches require much effort or expensive equipment to perform low-light image enhancement. For example, the image has to be captured in a raw camera file in order to be processed, and the addressing method does not perform well under extreme low-light conditions. In this paper, we propose a new convolutional network, Attention U-net (the integration of an attention gate and a U-net network), which is able to work on common file types (.PNG, .JPEG, .JPG, etc.) with primary support from deep learning to solve the problem of surveillance camera security in smart city inducements without requiring the raw image file from the camera, and it can perform under the most extreme low-light conditions.

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Chen, Yeong-Chin, Mariana Syamsudin y Sunneng S. Berutu. "Pretrained Configuration of Power-Quality Grayscale-Image Dataset for Sensor Improvement in Smart-Grid Transmission". Electronics 11, n.º 19 (26 de septiembre de 2022): 3060. http://dx.doi.org/10.3390/electronics11193060.

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The primary source of the various power-quality-disruption (PQD) concerns in smart grids is the large number of sensors, intelligent electronic devices (IEDs), remote terminal units, smart meters, measurement units, and computers that are linked by a large network. Because real-time data exchange via a network of various sensors demands a small file size without an adverse effect on the information quality, one measure of the power-quality monitoring in a smart grid is restricted by the vast volume of the data collection. In order to provide dependable and bandwidth-friendly data transfer, the data-processing techniques’ effectiveness was evaluated for precise power-quality monitoring in wireless sensor networks (WSNs) using grayscale PQD image data and employing pretrained PQD data with deep-learning techniques, such as ResNet50, MobileNet, and EfficientNetB0. The suggested layers, added between the pretrained base model and the classifier, modify the pretrained approaches. The result shows that advanced MobileNet is a fairly good-fitting model. This model outperforms the other pretraining methods, with 99.32% accuracy, the smallest file size, and the fastest computation time. The preprocessed data’s output is anticipated to allow for reliable and bandwidth-friendly data-packet transmission in WSNs.

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Xu, Yuanjin. "Application of Remote Sensing Image Data Scene Generation Method in Smart City". Complexity 2021 (28 de enero de 2021): 1–13. http://dx.doi.org/10.1155/2021/6653841.

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Remote sensing image simulation is a very effective method to verify the feasibility of sensor devices for ground observation. The key to remote sensing image application is that simultaneous interpreting of remote sensing images can make use of the different characteristics of different data, eliminate the redundancy and contradiction between different sensors, and improve the timeliness and reliability of remote sensing information extraction. The hotspots and difficulties in this direction are based on remote sensing image simulation of 3D scenes on the ground. Therefore, constructing the 3D scene model on the ground rapidly and accurately is the focus of current research. Because different scenes have different radiation characteristics, therefore, when using MATLAB to write a program generated by 3D scenes, 3D scenes must be saved as different text files according to different scene types, and then extension program of the scene is written to solve the defect that the calculation efficiency is not ideal due to the huge amount of data. This paper uses POV ray photon reverse tracking software to simulate the imaging process of remote sensing sensors, coordinate transformation is used to convert a triangle text file to POV ray readable information and input the RGB value of the base color based on the colorimetry principle, and the final 3D scene is visualized. This paper analyzes the thermal radiation characteristics of the scene and proves the rationality of the scene simulation. The experimental results show that introducing the chroma in the visualization of the scene model makes the whole scene have not only fidelity, but also radiation characteristics in shape and color. This is indispensable in existing 3D modeling and visualization studies. Compared with the complex radiation transmission method, using the multiple angle two-dimensional image generated by POV rays to analyze the radiation characteristics of the scene, the result is intuitive and easy to understand.

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Banerjee, S., F. Steenkeste, P. Couturier, M. Debray y A. Franco. "Telesurveillance of elderly patients by use of passive infra-red sensors in a 'smart' room". Journal of Telemedicine and Telecare 9, n.º 1 (1 de febrero de 2003): 23–29. http://dx.doi.org/10.1258/135763303321159657.

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We have developed an automated surveillance system based on passive infra-red sensors. Eight sensors were installed in a hospital room. A computer automatically captured data from the sensors every night from 21:00 until 06:00 the following morning. The sensors were polled twice per second and when a sensor was activated by movement, the event and time were recorded in a data file. At the end of the surveillance period the program analysed the data and generated a report showing the activities taking place in the room and their times. Four elderly patients were observed for a total of 97 nights. A total of 1637 possible sequences of movements by the patient and the hospital staff were detected. The computer was able to identify 1450 sequences (89%) correctly, in comparison with manual analysis. Only 10 movements (0.6%) were undetected by the system; all were very short sequences (five or six activations of the sensors). The system was generally capable of detecting and classifying all major movements in the room.

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Suseno, Taufiq Rizky Darmawan, Irawan Afrianto y Sufa Atin. "Strengthening data integrity in academic document recording with blockchain and InterPlanetary file system". International Journal of Electrical and Computer Engineering (IJECE) 14, n.º 2 (1 de abril de 2024): 1759. http://dx.doi.org/10.11591/ijece.v14i2.pp1759-1769.

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A diploma is a certificate or official document given by a school or college that is useful for continuing education, applying for jobs, and assessing student intelligence. The main problem with diplomas and other academic documents is that many are forged. This study aims to develop a prototype for recording student academic data using blockchain and blockchain and InterPlanetary file system (IPFS). The research stages were conducted with system conceptualization, data modeling, smart contract development, IPFS integration, data transaction development, user interface/user experience (UI/UX) development, and system testing. A blockchain is a permanent information structure formed by data blocks that are interconnected with transaction data blocks before and after it. The transaction data for each block are encrypted using asymmetric cryptography. IPFS is a peer-to-peer network protocol for storing and sharing data in a distributed file system applying the concept of decentralization to make the manipulation more difficult. The results show that student academic data and documents were successfully stored in a blockchain network using smart contracts and IPFS. Blockchain technology, smart contracts, and IPFS strengthen the value of these documents into documents that are safe, difficult to counterfeit, and easy to trace, such that authentication and integration are better preserved.

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Janhavi Satam. "Examination of Approaches for Identifying Vulnerabilities in Smart Contracts". Journal of Electrical Systems 20, n.º 4s (8 de abril de 2024): 2162–67. http://dx.doi.org/10.52783/jes.2322.

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Objective: By reviewing various previous works, this paper collects the multiple of approaches, strategies used to identify vulnerabilities in smart contracts. Blockchain is a decentralized technology that securely and immutably, records transactions across numerous computers in a visible manner. On a blockchain, smart contracts are self-executing agreements that independently execute and verify contract conditions. This reduces the need for middlemen and increases transparency. Smart contract vulnerabilities are problems in the code that could allow other parties to gain access to, alter, or steal assets as a result of mistakes, faults or imperfections made during development, thereby causing financial and operational harm. In this paper we have algorithms, techniques to detect vulnerabilities in smart contract using deep learning found in literature surveys. Methods: We have found some techniques using opcode, bytecode, Skip-Gram-Word2Vec to convert the smart contract file. Findings: We have found that LSTM, Vanilla-RNN, GRU have very less accuracy 49.64,53.68,54.54. Novelty & Applications: We will come with some different algorithms that will understand different vulnerability with more accuracy. We have come with CNN, Xception, EfficientNet-B2 which has accuracy high then LSTM, Vanilla-RNN, GRU i.e.71,69,75 percent.

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Yu, LiWei, Lei Zhang y Zhen Gong. "An Optimization Model for Landscape Planning and Environmental Design of Smart Cities Based on Big Data Analysis". Scientific Programming 2022 (20 de abril de 2022): 1–12. http://dx.doi.org/10.1155/2022/2955283.

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This paper adopts “digital landscape design logic,” analyzes and researches smart city and digital landscape design, and builds a digital city based on design logic, design basis, environment analysis, and results in a presentation based on the dilemma of landscape garden planning and design at this stage and the development trend of the smart garden and digital landscape design. The optimization model of the landscape and environment design is constructed based on design logic, design basis, environment analysis, and result presentation. First, on the Hadoop distributed computing platform based on the MapReduce parallel processing framework, we implement the massive small file processing methods (Hadoop Archives, CombineFileInputFormat, and Sequence Files) to compensate for the inherent defects of Hadoop and experimentally compare the memory consumption and execution efficiency of the three methods to propose a choice. The memory consumption and execution efficiency of the three methods are experimentally compared to propose a selection strategy. Finally, based on the MR-PFP algorithm, we parallelize the frequent itemset in-cab trajectory big data to generate interesting strong association rules. The experimental results show that the MR-PFP algorithm has better speedup ratio performance and higher mining efficiency than the parallel frequent pattern (PFP) growth algorithm. The research and analysis focused on the digital implementation of the standalone environmental analysis, using Rhino software and Grasshopper visual programming language to build parametric logic, establish parametric analysis models, and conduct a comprehensive analysis of the current environment. The study explores the use of digital landscape design methods and technologies in the landscape design process. Using Rhino + Grasshopper parametric and visualization programming software, we built parametric analysis models around elevation, slope, slope direction, water catchment, and viewable area and used mapping and overlay techniques to quantify the urban space. Finally, the purpose of collecting, monitoring, analyzing, simulating, creating, and reproducing landscape information is achieved.

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Mankar, Ishan. "Smart Surveillance System Using RESNET-50 and MTCNN". International Journal for Research in Applied Science and Engineering Technology 12, n.º 5 (31 de mayo de 2024): 4380–86. http://dx.doi.org/10.22214/ijraset.2024.62554.

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Abstract: In recent years, advances in computer vision and artificial intelligence have led to the development of sophisticated surveillance systems capable of tracking and identifying individuals in a variety of situations. This research presents a new intelligent surveillance system designed to track multiple people in a video and generate a comprehensive log file to keep records of identified people. The proposed system integrates state-of-the-art techniques in face detection and recognition to achieve accurate and efficient identification of people in video streams. The system uses a custom dataset collected using a script, which captures images of individuals' faces in various conditions and environments, and fine-tunes a pre-trained ResNet50 model for face recognition tasks.In addition, face detection is performed using the MTCNN (Multi-Task Cascade Convolutional Neural Network) algorithm, which ensures robust face detection under various conditions. The intelligent tracking system works by analyzing each frame of the input video, detecting faces using the MTCNN algorithm, and then identifying individuals using a trained face recognition model. Identified individuals are logged with a time stamp, providing a comprehensive record of their presence in the surveillance area over time

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Horvath, Kaleb, Mohamed Riduan Abid, Thomas Merino, Ryan Zimmerman, Yesem Peker y Shamim Khan. "Cloud-Based Infrastructure and DevOps for Energy Fault Detection in Smart Buildings". Computers 13, n.º 1 (16 de enero de 2024): 23. http://dx.doi.org/10.3390/computers13010023.

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We have designed a real-world smart building energy fault detection (SBFD) system on a cloud-based Databricks workspace, a high-performance computing (HPC) environment for big-data-intensive applications powered by Apache Spark. By avoiding a Smart Building Diagnostics as a Service approach and keeping a tightly centralized design, the rapid development and deployment of the cloud-based SBFD system was achieved within one calendar year. Thanks to Databricks’ built-in scheduling interface, a continuous pipeline of real-time ingestion, integration, cleaning, and analytics workflows capable of energy consumption prediction and anomaly detection was implemented and deployed in the cloud. The system currently provides fault detection in the form of predictions and anomaly detection for 96 buildings on an active military installation. The system’s various jobs all converge within 14 min on average. It facilitates the seamless interaction between our workspace and a cloud data lake storage provided for secure and automated initial ingestion of raw data provided by a third party via the Secure File Transfer Protocol (SFTP) and BLOB (Binary Large Objects) file system secure protocol drivers. With a powerful Python binding to the Apache Spark distributed computing framework, PySpark, these actions were coded into collaborative notebooks and chained into the aforementioned pipeline. The pipeline was successfully managed and configured throughout the lifetime of the project and is continuing to meet our needs in deployment. In this paper, we outline the general architecture and how it differs from previous smart building diagnostics initiatives, present details surrounding the underlying technology stack of our data pipeline, and enumerate some of the necessary configuration steps required to maintain and develop this big data analytics application in the cloud.

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Yang, Ting, Guanghua Zhang, Yin Li, Yiyu Yang, He Wang y Yuqing Zhang. "Detecting Privacy Leakage of Smart Home Devices through Traffic Analysis". Security and Communication Networks 2022 (15 de julio de 2022): 1–10. http://dx.doi.org/10.1155/2022/5655314.

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Under the management of the Internet of Things platform, smart home devices can be operated remotely by users and greatly facilitate people’s life. Currently, smart home devices have been widely accepted by consumers, and the number of smart home devices is rising rapidly. The increase of smart home devices introduces various security hazards to users. Smart home devices are vulnerable to side-channel attacks based on network traffic. The event of smart home devices can be identified by network surveillants. Given this situation, we designed a set of standardized workflows for traffic capturing, fingerprint feature extraction, and fingerprint event detection. Based on such workflow, we present IoTEvent, a semiautomatic tool to detect vulnerable smart home devices, which is not limited to specific types of communication protocols. IoTEvent first collects device traffic by simulating touch events for App. Then, it pairs the packet sequences with events and generates a signature file. We also test the usability and performance of IoTEvent on five cloud platforms of smart home devices. Finally, we discuss the reasons for privacy leakage of smart home devices and security countermeasures.

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Durner, Dominik, Badrish Chandramouli y Yinan Li. "Crystal". Proceedings of the VLDB Endowment 14, n.º 11 (julio de 2021): 2432–44. http://dx.doi.org/10.14778/3476249.3476292.

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Cloud analytical databases employ a disaggregated storage model, where the elastic compute layer accesses data persisted on remote cloud storage in block-oriented columnar formats. Given the high latency and low bandwidth to remote storage and the limited size of fast local storage, caching data at the compute node is important and has resulted in a renewed interest in caching for analytics. Today, each DBMS builds its own caching solution, usually based on file-or block-level LRU. In this paper, we advocate a new architecture of a smart cache storage system called Crystal , that is co-located with compute. Crystal's clients are DBMS-specific "data sources" with push-down predicates. Similar in spirit to a DBMS, Crystal incorporates query processing and optimization components focusing on efficient caching and serving of single-table hyper-rectangles called regions. Results show that Crystal, with a small DBMS-specific data source connector, can significantly improve query latencies on unmodified Spark and Greenplum while also saving on bandwidth from remote storage.

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Dheyaa Ismael, Khansaa y Stanciu Irina. "Face recognition using viola-jones depending on python". Indonesian Journal of Electrical Engineering and Computer Science 20, n.º 3 (1 de diciembre de 2020): 1513. http://dx.doi.org/10.11591/ijeecs.v20.i3.pp1513-1521.

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In this paper, the proposed software system based on face recognition the proposed system can be implemented in the smart building or any VIP building need security interring in general, The human face will be recognized from a stream of pictures or video feed, this technology recognizes the person according to the specific algorithm, the algorithm that employed in this paper is the Viola–Jones object detection framework by using Python. The task of the proposed facial recognition system consists of two steps, the first one was detected the human face from live video using the webcamera in the computer, and the second step recognizes if this face allowed to enter the building or not by comparing it with the existing database, the two steps depending on the OpenCV python by importing cv2 method for detecting the human face, the frames can be read or written to file with the cv2.imread and cv2.imwrite functions respectively Finally, this proposed software system can be used to control access in smart buildings as a rule and the advancement of techniques connected around there, Providing a security system is one of the most important features must be achieved in the smart buildings, this proposed system can be used as an application in a smart building as a security system. Face recognition is one of the most important applications using today for practical facial recognition, The proposed software system, depending on using OpenCV (Open Source Computer Vision) is a popular computer vision library, in 1999 this library started by Intel. The platform library sets its focus on real-time image processing and includes patent-free implementations of the latest computer vision algorithms. OpenCV 2.3.1 now comes with a programming interface to C, C++, Python, and Android. OpenCV library of python, the three algorithms that will be used in this proposed system. The currently available algorithms are:Eigenfaces → createEigenFaceRecognizer()Fisherfaces → createFisherFaceRecognizer()Local Binary Patterns Histograms → createLBPHFaceRecognizer()Finally the proposed system provide entering to the building just for the authorized person according to face recognition algorithem.

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Tanveer Baig, Z. y Chandrasekar Shastry. "Smart Hybridized Routing Protocol for Animal Monitoring and Tracking Applications". Scalable Computing: Practice and Experience 23, n.º 4 (23 de diciembre de 2022): 339–49. http://dx.doi.org/10.12694/scpe.v23i4.2040.

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Wireless sensor networks (WSN) have been exploited for {countless} application domains, most notably the surveillance of environments and habitats, which has already become a critical mission. As a result, WSNs have been implemented to monitor animal care and track their health status. However, excessive energy utilization and communication traffic on packet transmissions lead to system deterioration, especially whenever perceived information captured in the monitoring area is transferred to the access point over multiple dynamic sinks. Further to manage the energy and data transmission issue, the energy consumption and location aware routing protocol has been architected on the wireless Nano sensor nodes. In this article, a novel hybrid energy and location aware routing protocol to cloud enabled IoT based Wireless Sensor Network towards animal health monitoring and tracking has been proposed. However proposed data routing protocol incorporates the trace file for path selection for data transmission to base station using sink node. Trace file has been obtained on processing the cluster heads established in the network. Therefore, clustering of node in the network has to be achieved using LEACH protocol which enhances the network scalability and network lifetime by clustering the nodes with Metaheuristics constraints like location or node density comparability. The objective of the proposed model is to enhance the network scalability and energy consumption by establishing the multiple node clusters with high density cluster head through Metaheuristics Node Clustering optimization techniques. Metaheuristics based node clustering is been obtained using Improved Particle Swarm Optimization. Further it is employed to compute the optimal path for sensed data transmission to base station. Node clustering provides high energy consumption among the sensing nodes and to establish the high energy clusters towards sensed information dissemination to base station on dynamically reforming the nodes clusters with respect to Node density and node location. Simulation analysis of the proposed energy efficient routing protocol provides high performance in energy utilization, packet delivery ratio, packet loss and Average delay compared against the conventional protocols on propagation of the data through sink node to base station

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Schwarz, Franziska, Klaus Schwarz, Daniel Fuchs, Reiner Creutzburg y David Akopian. "Firmware Vulnerability Analysis of Widely Used Low-Budget TP-Link Routers". Electronic Imaging 2021, n.º 3 (18 de junio de 2021): 135–1. http://dx.doi.org/10.2352/issn.2470-1173.2021.3.mobmu-135.

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TP-Link Technologies Co, Ltd. is a Chinese manufacturer of networking products and has a 42% share of the consumer WLAN market, making it the market leader. The company sells about 150 million devices per year. Many people worldwide use the Internet every day and are connected to the Internet with their computers. In the world of smart homes, even coffee machines, refrigerators, smart sockets, and light bulbs have found their way to the Internet, not to mention the many smartphones, which are, of course, also connected to the Internet. Since many different dangers come from a heater or printer and the many other smart devices directly connected to the Internet, there is a safe haven: the local area network. To connect to the Internet, one needs a modem, which is built into a router in many cases. Routers route network packets back and forth between several computer networks. They are used to connect to the Internet, and they are the bridge between the home network and the Internet in almost every household connected to the Internet. Because of their nature as a bridge between local and global networks, they are also the largest attack vector. [19] This paper examines how up-to-date the firmware of standard home network routers is and how secure the firmware is. In order to obtain a representative result, the examined routers were selected according to fixed rules. Each router had to be a product of the manufacturer TP-Link, the routers had to be in the low-budged range (less than 20 Euro) and be available from Amazon. Also, two different types of investigations were identified for the selected devices. Firstly, the devices were examined in the form of physically existing hardware, and secondly, an attempt was made to access the firmware via the manufacturer’s website. It was found that even the fixing of current vulnerabilities and recently released update files are no guarantee that older vulnerabilities have been fixed. Secrets such as private keys and certificates are hard-coded in the firmware and can be extracted from update files. Moreover, devices are deliberately built to make it impossible to install the latest alternative firmware.

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Alhaddad, Mohammed J., Monagi H. Alkinani, Mohammed Salem Atoum y Alaa Abdulsalm Alarood. "Evolutionary Detection Accuracy of Secret Data in Audio Steganography for Securing 5G-Enabled Internet of Things". Symmetry 12, n.º 12 (14 de diciembre de 2020): 2071. http://dx.doi.org/10.3390/sym12122071.

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With the unprecedented growing demand for communication between Internet of Things (IoT) devices, the upcoming 5G and 6G technologies will pave the path to a widespread use of ultra-reliable low-latency applications in such networks. However, with most of the sensitive data being transmitted over wireless links, security, privacy and trust management are emerging as big challenges to handle. IoT applications vary, from self-driving vehicles, drone deliveries, online shopping, IoT smart cities, e-healthcare and robotic assisted surgery, with many applications focused on Voice over IP (VoIP) and require securing data from potential eavesdroppers and attackers. One well-known technique is a hidden exchange of secret data between the devices for which security can be achieved with audio steganography. Audio steganography is an efficient, reliable and low-latency mechanism used for securely communicating sensitive data over wireless links. MPEG-1 Audio Layer 3’s (MP3’s) bit rate falls within the acceptable sound quality required for audio. Its low level of noise distortion does not affect its sound quality, which makes it a good carrier medium for steganography and watermarking. The strength of any embedding technique lies with its undetectability measure. Although there are many detection techniques available for both steganography and watermarking, the detection accuracy of secret data has been proven erroneous. It has yet to be confirmed whether different bit rates or a constant sampling rate for embedding eases detection. The accuracy of detecting hidden information in MP3 files drops with the influence of the compression rate or increases. This drop or increase is caused by either the increase in file track size, the sampling rate or the bit rate. This paper presents an experimental study that evaluates the detection accuracy of the secret data embedded in MP3. Training data were used for the embedding and detection of text messages in MP3 files. Several iterations were evaluated. The experimental results show that the used approach was effective in detecting the embedded data in MP3 files. An accuracy rate of 97.92% was recorded when detecting secret data in MP3 files under 128-kbps compression. This result outperformed the previous research work.

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Patil, Anand N. y Sujata V. Mallapur. "Novel machine learning based authentication technique in VANET system for secure data transmission". Journal of Autonomous Intelligence 6, n.º 2 (8 de agosto de 2023): 828. http://dx.doi.org/10.32629/jai.v6i2.828.

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Adaptive transport technologies based on vehicular ad hoc networks (VANET) has proven considerable potential in light of the developing expansion of driver assistance and automobile telecommunication systems. However, confidentiality and safety are the vital challenges in vehicular ad hoc networks which could be seriously impaired by malicious attackers. While protecting vehicle privacy from threats, it is imperative to stop internal vehicles from putting out bogus messages. Considering these issues, a novel machine learning based message authentication combined with blockchain and inter planetary file system (IPFS) is proposed to achieve message dissemination in a secured way. Blockchain is the emerging technology which attempts to solve these problems by producing tamper proof events of records in a distributed environment and inter planetary file system used in the framework is a protocol designed to store the event with content addressability. Along with this combined technology, the source metadata information collected from the inter planetary file system is stored via a smart contract and uploaded to the distributed ledger technology (DLT). For performing event authentication, K-means clustering and support vector machine (SVM) classifier is employed in this framework. K-means clustering performs clustering of vehicles and it is marked malicious or not malicious. After clustering, support vector machine classifier detects the malicious event messages. By this way, the malicious messages are identified and it is dropped. Only the secure messages are forwarded in the network. Finally, our approach is capable of creating a safe and decentralized vehicular ad hoc network architecture with accountability and confidentiality through theoretical study and simulations.

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Dozias, Anne, Cristian Camilo Otalora-Leguizamón, Marco Bianchetti y Maria Susana Avila-Garcia. "Smart pens to assist fibre optic sensors research: Evaluating OCR tools". Avances en Interacción Humano-Computadora, n.º 1 (31 de octubre de 2018): 41. http://dx.doi.org/10.47756/aihc.y3i1.42.

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Reproducibility is one of the big challenges in research. Lab notebooks have been used to record data, observations and relevant remarks of the research processes. Smart pens are devices that record audio, handwriting notes thanks to micro patterned paper, and generate pdf files and audio enriched notes (pencasts). The handwriting notes can then be processed using optical character recognition (OCR) software to generate digital documents allowing the user to archive and access these notes in an easier way. However, OCR for handwriting is still a challenge in the computer vision research area. In this paper, we report the evaluation results of different OCR tools when processing handwriting notes written by 7 participants focusing on the main elements and technical vocabulary identified in fibre optic sensors research.

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Pinheiro, Alexandre, Edna Dias Canedo, Rafael Timoteo De Sousa y Robson De Oliveira Albuquerque. "Monitoring File Integrity Using Blockchain and Smart Contracts". IEEE Access 8 (2020): 198548–79. http://dx.doi.org/10.1109/access.2020.3035271.

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32

Ciorap, Mariana, Dogan Gures y Cătălin Gabriel Dumitraş. "A Computer Aided Design Software Comparative Study with Applications in Industry 4.0 – Smart Manufacturing". Bulletin of the Polytechnic Institute of Iași. Machine constructions Section 68, n.º 1 (1 de marzo de 2022): 47–68. http://dx.doi.org/10.2478/bipcm-2022-0004.

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Abstract The concept Industry 4.0 implies many elements such as CAD/CAM/CAE, simulation, additive fabrication, IoT (internet of things) and it was a result of the demands of the industry in decreasing the period of product designing, flexibility of the design, and quick response to the market demands.. With the help of CAD software, the design period for a new product was reduced by almost 30 percent. Based on this reason, the CAD software family was developed during the last twenty years giving the possibility to create more complex 3D models, parametrization and calculus for product cost or mechanical properties. One of the major drawback in having such a great number of companies that produce CAD software is that each one tries to individualize their own software. We can mention that there are over 150 types of CAD files format. This multitude of types of CAD software makes it necessary to carry out a comparative study to establish criteria for choosing one software or another. In this article we carried out such a study considering three of the most used software based on a case study – the design of a turning cutting tool.

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Iacobescu, Ciprian, Gabriel Oltean, Camelia Florea y Bogdan Burtea. "Unified InterPlanetary Smart Parking Network for Maximum End-User Flexibility". Sensors 22, n.º 1 (29 de diciembre de 2021): 221. http://dx.doi.org/10.3390/s22010221.

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Technological breakthroughs have offered innovative solutions for smart parking systems, independent of the use of computer vision, smart sensors, gap sensing, and other variations. We now have a high degree of confidence in spot classification or object detection at the parking level. The only thing missing is end-user satisfaction, as users are forced to use multiple interfaces to find a parking spot in a geographical area. We propose a trustless federated model that will add a layer of abstraction between the technology and the human interface to facilitate user adoption and responsible data acquisition by leveraging a federated identity protocol based on Zero Knowledge Cryptography. No central authority is needed for the model to work; thus, it is trustless. Chained trust relationships generate a graph of trustworthiness, which is necessary to bridge the gap from one smart parking program to an intelligent system that enables smart cities. With the help of Zero Knowledge Cryptography, end users can attain a high degree of mobility and anonymity while using a diverse array of service providers. From an investor’s standpoint, the usage of IPFS (InterPlanetary File System) lowers operational costs, increases service resilience, and decentralizes the network of smart parking solutions. A peer-to-peer content addressing system ensures that the data are moved close to the users without deploying expensive cloud-based infrastructure. The result is a macro system with independent actors that feed each other data and expose information in a common protocol. Different client implementations can offer the same experience, even though the parking providers use different technologies. We call this InterPlanetary Smart Parking Architecture NOW—IPSPAN.

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S. Jadhav, Vilas, Somnath A Wankhede, Priyanka B. Nikam y Anil L. Tidar. "Greenhouse Monitoring and Controlling Using LabVIEW Automation". Journal of Control System and Control Instrumentation 9, n.º 3 (2023): 27–33. http://dx.doi.org/10.46610/jocsaci.2023.v09i03.005.

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Traditional greenhouses need to regulate or monitor and control the climactic condition changes to grow healthy plants and other crops. A greenhouse control system should ideally include data collecting, transmission, and remote monitoring. This paper design a system of a model that controls and monitor the temperature, light intensity and soil moisture level right and left side of the soil by sensing the values from sensors and controlling the temperature, and moisture of the soil using one fan, water pumps accordingly. Monitoring and controlling a greenhouse environment collects data from sensors that affect the pace of growth of healthy plants. The system has several physical characteristics to measure, including temperature, light intensity, and moisture. These parameters were sensed using sensors and current/live data was supplied to a computer software Lab view application using an NI DAQ card. Using these measured parameters, save it in a notepad file format and then use Excel to analyze the data for any system or greenhouse modifications or corrections. Recently, the market has seen significant advancements in the automation business. Automation is involved in every sector such as in smart homes, smart industry, and smart agriculture. Greenhouses are a significant means for farmers in rural and urban regions to benefit from automatic monitoring and management of greenhouse environment parameters, which will replace direct human monitoring.

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Mohammed, Marwa Sami y Asaad Noori Hashim. "Protect medical records by using blockchain technology". Indonesian Journal of Electrical Engineering and Computer Science 32, n.º 1 (1 de octubre de 2023): 342. http://dx.doi.org/10.11591/ijeecs.v32.i1.pp342-352.

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Recently, medical records have been stored and shared locally, which creates a risk of data loss or corruption; these records may be stored and shared through cloud-based central data centers; nonetheless, this strategy has disadvantages, such as the need for significant storage space and the privacy concerns associated with network-wide data sharing. Medical records require increased security and confidentiality, furthermore, these records must be protected when transmitted to and shared with doctors of the same specialization, to solve this problem, blockchain technology was used as a decentralized technology that offers a secure and immutable way to store and protect information. In this paper, a website is designed that uses blockchain technology to save medical records and employs smart contract technology in the ethereum blockchain to govern the creation and display of files and sharing. An interplanetary file system was used to offer a mechanism for the decentralized storage of medical images and reports while maintaining their accessibility on a global scale, it is available only for doctors who have the authority to access them, and the proposed system proved efficient in saving and sharing medical records with high security and less cost.

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Palaiokrassas, Georgios, Petros Skoufis, Orfefs Voutyras, Takafumi Kawasaki, Mathieu Gallissot, Radhouene Azzabi, Akira Tsuge et al. "Combining Blockchains, Smart Contracts, and Complex Sensors Management Platform for Hyper-Connected SmartCities: An IoT Data Marketplace Use Case". Computers 10, n.º 10 (16 de octubre de 2021): 133. http://dx.doi.org/10.3390/computers10100133.

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In this paper, we demonstrate the multiple points of innovation when combining blockchain technology with Internet of Things (IoT) and security frameworks. The deployment and use of IoT device networks in smart city environments has produced an enormous amount of data. The fact that those data are possessed by multiple sources that use independent systems for data collection, storage, and use impedes the exploitation of their value. Blockchains, as distributed ledgers, can be used for addressing the development of a universal system for data collection and distribution. Smart contracts can be used to automate all the processes of such a network, while at the same time, blockchain and the InterPlanetary File System (IPFS) protect sensitive data through anonymity and distributed storage. An innovative and open IoT blockchain market of applications, data, and services is proposed that: (i) provides the framework upon which objects and people can exchange value in form of virtual currencies, for assets (data and services) received; (ii) defines the motivation incentives according to social and business context for humans and smart objects to interact. The specific marketplace is piloted through a cross-border trial between Santander and Fujisawa, in the context of the M-Sec project, validating thus the interoperability, efficiency, and data protection principles.

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Patel, Ochchhav y Hiren Patel. "Enhancing Data Security in Healthcare IoT: An Innovative Blockchain-based Solution". International Journal on Recent and Innovation Trends in Computing and Communication 11, n.º 10s (7 de octubre de 2023): 69–80. http://dx.doi.org/10.17762/ijritcc.v11i10s.7597.

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The Internet of Things (IoT) has revolutionized the healthcare industry by enabling the seamless integration of medical devices, sensors, and data-driven applications. However, the large influx of sensitive healthcare data and the proliferation of linked devices have caused grave worries about data security and privacy. Traditional centralized security systems are unable to handle the changing threats and problems in the IoT healthcare setting. This study suggests a novel strategy for boosting data security in the healthcare industry that makes use of blockchain technology. The main goal of this research is to develop and deploy a trustworthy framework that safeguards private healthcare information in IoT networks. Blockchain, as a distributed and decentralized ledger, offers inherent security features such as immutability, transparency, and cryptographic mechanisms. In this research, it is suggested that healthcare data be gathered via the IoT and stored in the Interplanetary File System (IPFS) using Ethereum-based blockchain technology for data security. The suggested method creates a reliable environment for managing healthcare data by exploiting the special features of blockchain. The json and jpeg files are utilized five times on a distributed database housed on IPFS and a centralized database hosted on Firebase, and the upload and download times are recorded. For IoT-based healthcare systems, we have also investigated the cost and length of time required to implement smart contracts on blockchain platforms like Rinkeby, Binance, and Matic. This research suggests implementing the Blockchain platform in an IoT-based healthcare system to provide data confidentiality, integrity, and accessibility.

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Kaneriya, Jayana y Hiren Patel. "A Secure and Privacy-Preserving Student Credential Verification System Using Blockchain Technology". International Journal of Information and Education Technology 13, n.º 8 (2023): 1251–60. http://dx.doi.org/10.18178/ijiet.2023.13.8.1927.

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Advancements in digital technologies have made the storage, sharing, and verification of educational credentials extremely important for entities such as students, universities, institutions, and companies. Digital credentials play an important role in students’ lives as a lifelong learning passport. The educational field is experiencing numerous issues such as academic record forgery, record misuse, credential data tampering, time-consuming verification procedures, and issues related to ownership and control. Modern-day technology, Blockchain, is an appropriate alternative to resolve these issues and increase trust among entities. In this research, we intend to propose a Blockchain-based educational digital credential issuance, and verification model that addresses these issues in the education system using Ethereum Blockchain and smart contracts. The method we propose offers a way to demonstrate the correctness of specific credential attributes without revealing other attributes, thereby leading to ownership, minimal disclosure, and control. We offer an interface for storing massively encrypted academic records in a decentralized file system like Interplanetary File System (IPFS). Furthermore, Ethereum provides tamper-resistant chains to maintain the integrity of digital credentials. Finally, in comparison with the time it requires to issue credentials, our model safely accelerates the verification process by about 8%.

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Rahaman, Major Muhammad Masudur. "Recent Advancement of Cyber Security: Challenges and Future Trends in Bangladesh". Saudi Journal of Engineering and Technology 7, n.º 6 (6 de julio de 2022): 278–89. http://dx.doi.org/10.36348/sjet.2022.v07i06.002.

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The massive demand for global transformations describes the necessity of high-speed communication in the twenty-first century. Almost every facet of online networks is changing, including international relations, politics, trade, and security. However, cyber security has become a major issue all around the world. Bangladesh has recently taken the required steps to address the problem as swiftly as feasible. In order to prevent and combat cyber threats, the government of Bangladesh plans to establish a specialized computer incident response team (CIRT) for banks and financial institutions, which will serve as the national response team responsible for receiving, reviewing, and responding to computer security incidents and activities in Bangladesh. Implementing strong and multilayer authentication to better management of the data, as well as discovering and mapping out security issues, some major initiatives are required to implement cyber security. Engineers should obtain hands-on training in decoding corrupted data files during any cyber-attack in order to recover data from any lost data. In this review, cyber security challenges in smart cities and smart governance have been examined, with an emphasis on e-commerce, machine learning, industry automation, IoT, and other security elements. The main cyber security concerns are discussed in order to better comprehend almost every necessity of long-term cyber security situations. Moreover, smart industry control and its security infrastructure, problems for implementation in Bangladesh and recent security issues have been highlighted.

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Wang, Lixin, Wenlei Sun, Jintao Zhao, Xuedong Zhang, Cheng Lu y Hao Luo. "A Non-Fungible Token and Blockchain-Based Cotton Lint Traceability Solution". Applied Sciences 14, n.º 4 (17 de febrero de 2024): 1610. http://dx.doi.org/10.3390/app14041610.

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As a critical raw material for the textile industry, cotton lint provides various types of cotton yarns, fabrics and finished products. However, due to the complexity of the supply chain and its many links, information records are often missing, inaccurate or lagging, resulting in low transparency and traceability. In the traditional cotton lint supply chain, the data of each link are stored in isolation; due to the lack of an effective sharing mechanism and the formation of “information silos”, complete traceability is challenging to achieve. In addition, the completeness and authenticity of documents such as lint quality reports and certificates of origin must be rapidly strengthened. Otherwise, quality problems may arise. To solve the above problems, this study proposes a cotton lint supply chain traceability system based on blockchain and non-fungible tokens (NFTs), covering the whole cotton lint production process from harvesting to selling. We use an NFT as an asset token to digitise seed cotton, cotton lint and quality inspection reports and allow participants to store and manage these assets on the blockchain. The system design includes architecture diagrams, sequence diagrams and Ethernet smart contract development based on the ERC721 standard. In addition, the integration of Interplanetary File System (IPFS) technology solves the problem of storing large files on the chain and ensures that the data are permanently preserved and cannot be tampered with. We provide a diagram of the interactions between the system components and the four core algorithms’ design, testing and verification process. We present an in-depth analysis of the solution regarding the transaction costs and smart contract security. We confirm the solution’s security, reliability and applicability through a cost evaluation and security analysis.

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Wen, Shengwei. "A study on the big data scientific research model and the key mechanism based on blockchain". Open Computer Science 12, n.º 1 (1 de enero de 2022): 357–63. http://dx.doi.org/10.1515/comp-2022-0258.

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Abstract In an era of open data sharing, the scientific research field puts forward an urgent need for the value of big data. However, big data still form “data islands,” which seriously affects the level of scientific research and the progress of scientific research. In this regard, this article proposes the research and realization of the big data scientific research model and key mechanism based on blockchain. This article uses the K-means algorithm to cluster scientific research data and reasonably utilizes the decentralization, smart contracts, and non-tampering characteristics of the blockchain to design a distributed data model based on the blockchain. This article proposes that a BIZi network is formed based on a blockchain Interplanetary File System (IPFS) and Zigzag code (blockchain, IPF Sand Zigzag code, BIZi for short) to achieve reliable data connection and through a set of data access control mechanisms and data service customization mechanism to effectively provide data requirements for scientific research. Finally, IPFS network transmission speed performance can better meet the needs of scientific research. The larger the number of file blocks, the higher the fault tolerance rate of the scheme and the better the storage efficiency. In a completely open data-sharing scenario, the fault tolerance rate of Byzantine nodes is extremely high to ensure the stability of the blockchain. The current optimal consensus algorithm fault tolerance rate reaches 49%.

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Sung, Huang-Chih. "Prospects and challenges posed by blockchain technology on the copyright legal system". Queen Mary Journal of Intellectual Property 9, n.º 4 (diciembre de 2019): 430–51. http://dx.doi.org/10.4337/qmjip.2019.04.04.

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In the current copyright law and technology environment, two prominent problems must be considered when enforcing and executing copyrights: (i) the difficulty of proving authorship/ownership of a copyright; and (ii) the difficulty of conducting copyright transactions. The invention of blockchain technology has made it possible to solve these two issues. First, the use of blockchain technology with the InterPlanetary File System (IPFS) is an excellent mechanism for copyright authentication and document preservation. This mechanism allows authors (copyright owners) to prove authorship of their works and copyrights ownership. However, this mechanism for copyright authentication and document preservation may not be applicable in the future primarily because the computer software currently used may be upgraded in the following years. Second, the combination of Ethereum Blockchain and smart contracts can reduce transaction costs and enhance the efficiency of copyright assignments and licensing transactions. However, many legal problems regarding smart contracts have yet to be addressed. These problems include identifying the contracting parties in the anonymous blockchain network, dealing with scenarios where both contracting parties want to amend the implemented smart contracts, explaining code-based smart contracts and setting up an internal dispute resolution mechanism. Unlike the traditional transmission control protocol/Internet protocol network, where any activity is traceable, users on blockchain technology remain anonymous and their activities on the blockchain are hardly traceable. Although the blockchain itself is unlikely to become a hotbed of copyright infringement, the combination of the Ethereum Blockchain, the IPFS and smart contracts may make the entire process a hotbed of copyright infringement. Therefore, this situation poses considerable worries regarding copyright infringement on the blockchain. When the decentralized and anonymized blockchain and peripheral technologies mature, they will have considerable influence on copyright protection. This problem must be addressed by the copyright legal system in the current wave of blockchain technology implementation.

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43

Lyon, Warrick y Peter De Joux. "A Tracking System for Sharks in Shallow Water". Marine Technology Society Journal 48, n.º 6 (1 de noviembre de 2014): 14–20. http://dx.doi.org/10.4031/mtsj.48.6.2.

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AbstractA shallow-water shark tracking system was developed to track a floating tag towed behind a medium-sized shark as it swims around a shallow water estuary. The towed float contains a GPS receiver, an Arduino Fio microcontroller, and an XBee Pro (low-powered digital radio transceiver module) for radio frequency (RF) transmissions. The receiving system uses XBee Pros as RF routers, positioned through the estuary, to act as a self-healing mesh network, passing the tag signals back to a coordinating XBee Pro attached to the serial port of a land-based PC. A Python script filters good GPS positions from bad and builds Google Earth Keyhole Markup Language (KML) files. The Google Earth files, loaded from the cloud, allow easy access for biologists with smart phones to access real-time shark positional data. The computer sends emails when tag positional data show a shark leaving the estuary so the tags can be retrieved and also when router or tag battery voltage gets too low and needs replacing.

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44

Tayeb, Shahab, Neha Raste, Matin Pirouz y Shahram Latifi. "A Cognitive Framework to Secure Smart Cities". MATEC Web of Conferences 208 (2018): 05001. http://dx.doi.org/10.1051/matecconf/201820805001.

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The advancement in technology has transformed Cyber Physical Systems and their interface with IoT into a more sophisticated and challenging paradigm. As a result, vulnerabilities and potential attacks manifest themselves considerably more than before, forcing researchers to rethink the conventional strategies that are currently in place to secure such physical systems. This manuscript studies the complex interweaving of sensor networks and physical systems and suggests a foundational innovation in the field. In sharp contrast with the existing IDS and IPS solutions, in this paper, a preventive and proactive method is employed to stay ahead of attacks by constantly monitoring network data patterns and identifying threats that are imminent. Here, by capitalizing on the significant progress in processing power (e.g. petascale computing) and storage capacity of computer systems, we propose a deep learning approach to predict and identify various security breaches that are about to occur. The learning process takes place by collecting a large number of files of different types and running tests on them to classify them as benign or malicious. The prediction model obtained as such can then be used to identify attacks. Our project articulates a new framework for interactions between physical systems and sensor networks, where malicious packets are repeatedly learned over time while the system continually operates with respect to imperfect security mechanisms.

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45

Brunner, Kilian, Stephen Dominiak y Martin Ostertag. "Application of G.hn Broadband Powerline Communication for Industrial Control Using COTS Components". Technologies 11, n.º 6 (10 de noviembre de 2023): 160. http://dx.doi.org/10.3390/technologies11060160.

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Broadband powerline communication is a technology developed mainly with consumer applications and bulk data transmission in mind. Typical use cases include file download, streaming, or last-mile internet access for residential buildings. Applications gaining momentum are smart metering and grid automation, where response time requirements are relatively moderate compared to industrial (real-time) control. This work investigates to which extent G.hn technology, with existing, commercial off-the-shelf components, can be used for real-time control applications. Maximum packet rate and latency statistics are investigated for different G.hn profiles and MAC algorithms. An elevator control system serves as an example application to define the latency and throughput requirements. The results show that G.hn is a feasible technology candidate for industrial IoT-type applications if certain boundary conditions can be ensured.

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46

Monteiro, Carlos y José Leal. "Managing experiments on cognitive processes in writing with HandSpy". Computer Science and Information Systems 10, n.º 4 (2013): 1747–73. http://dx.doi.org/10.2298/csis121130061m.

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Experiments on cognitive processes require a detailed analysis of the contribution of many participants. In the case of cognitive processes in writing, these experiments require special software tools to collect gestures performed with a pen or a stylus, and recorded with special hardware. These tools produce different kinds of data files in binary and proprietary formats that need to be managed on a workstation file system for further processing with generic tools, such as spreadsheets and statistical analysis software. The lack of common formats and open repositories hinders the possibility of distributing the workload among researchers within the research group, of re-processing the collected data with software developed by other research groups, and of sharing results with the rest of the cognitive processes research community. This paper describes the development of HandSpy, a collaborative environment for managing experiments in the cognitive processes in writing. This environment was designed to cover all the stages of the experiment, from the definition of tasks to be performed by participants, to the synthesis of results. Collaboration in HandSpy is enabled by a rich web interface. To decouple the environment from existing hardware devices for collecting written production, namely digitizing tablets and smart pens, HandSpy is based on the InkML standard, an XML data format for representing digital ink. This design choice shaped many of the features in HandSpy, such as the use of an XML database for managing application data and the use of XML transformations. XML transformations convert between persistent data representations used for storage and transient data representations required by the widgets on the user interface. Despite being a system independent from a specific collecting device, for the system validation, a framework for data collection was created. This framework has also been highlighted in the paper due to the important role it took in a data collection process, of a scientific project to study the cognitive processes involved in writing.

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47

Vásquez-Ramírez, Raquel, Maritza Bustos-Lopez, Giner Alor-Hernández, Cuauhtémoc Sanchez-Ramírez y Jorge García-Alcaraz. "AthenaCloud: A cloud-based platform for multi-device educational software generation". Computer Science and Information Systems 13, n.º 3 (2016): 957–81. http://dx.doi.org/10.2298/csis160807037v.

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Nowadays, information technologies play an important role in education. In education, mobile and TV applications can be considered a support tool in the teaching - learning process, however, relevant and appropriate mobile and TV applications are not always available; teachers can only judge applications by reviews or anecdotes instead of testing them. These reasons lead to the needs and benefits for creating one?s own mobile application for teaching and learning. In this work, we present a cloud-based platform for multi-device educational software generation (smartphones, tablets, Web, Android-based TV boxes, and smart TV devices) called AthenaCloud. It is important to mention that an open cloud-based platform allows teachers to create their own multi-device software by using a personal computer with Internet access. The goal of this platform is to provide a software tool to help educators upload their electronic contents - or use existing contents in an open repository - and package them in the desired setup file for one of the supported devices and operating systems.

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Naeem, Muhammad Rashid, Mansoor Khan, Ako Muhammad Abdullah, Fazal Noor, Muhammad Ijaz Khan, Muhammad Asghar Khan, Insaf Ullah y Shah Room. "A Malware Detection Scheme via Smart Memory Forensics for Windows Devices". Mobile Information Systems 2022 (3 de octubre de 2022): 1–16. http://dx.doi.org/10.1155/2022/9156514.

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With the introduction of 4G/5G Internet and the increase in the number of users, the malicious cyberattacks on computing devices have been increased making them vulnerable to external threats. High availability windows servers are designed to ensure delivery of consistent services such as business activities and e-services to their customers without any interruption. At the same time, a cyberattack on any of the clustered computer can put servers and customer devices in danger. A memory dump mechanism can capture the contents of memory in the event of a system or device crash such as corrupted files, damaged hardware, or irregular CPU power consumption. In this paper, we present a smart memory forensics scheme to recognize malicious attacks over high availability servers by capturing the memory dump of suspicious processes in the form of RGB visual images. Second, the local and global properties of malware images are captured using local binary patterns (LBP) and gray-level co-occurrence matrices (GLCM). A state-of-the-art t-distributed stochastic neighbor embedding scheme (t-SNE) is applied to reduce data dimensionality and improve the detection time of unknown malwares and their variants. An optimized CNN model is designed to predict malicious files harming servers or user devices. Throughout this study, we employed public data set of 4294 malicious samples covering malware variants and benign executables. A baseline is prepared to compare the performance of proposed model with state-of-the-art malware detection methods. The combined LBP + GLCM feature extraction along with t-SNE dimensionality reduction scheme further improved the detection accuracy by 98%, whereas the detection time is also increased by 73x. The overall performance shows that memory forensics is more effective for malware detection in terms accuracy and response time.

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Tusa, Francesco, Massimo Villari y Antonio Puliafito. "Credential Management Enforcement and Secure Data Storage in gLite". International Journal of Distributed Systems and Technologies 1, n.º 1 (enero de 2010): 76–97. http://dx.doi.org/10.4018/jdst.2010090805.

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This article describes new security solutions for Grid middleware, and specifically faces the issues related to the management of users’ and servers’ credentials, together with storing and secure data transmission in the Grid. Our work, built on Grid Security Infrastructure (GSI), provides new capabilities (i.e. smart card Grid access, and strong security file storage XML-based) to be used on top of different Grid middlewares, with a low level of changes. This work is currently implemented on gLite and accomplishes the access to Grid resources in a uniform and transparent way. These improvements enable the Grid computing toward the new processing model known as business services.

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50

Gómez-Marín, Ernesto, Davide Martintoni, Valerio Senni, Encarnación Castillo y Luis Parrilla. "Fine-Grained Access Control with User Revocation in Smart Manufacturing". Electronics 12, n.º 13 (27 de junio de 2023): 2843. http://dx.doi.org/10.3390/electronics12132843.

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Collaborative manufacturing is a key enabler of Industry 4.0 that requires secure data sharing among multiple parties. However, intercompany data-sharing raises important privacy and security concerns, particularly given intellectual property and business-sensitive information collected by many devices. In this paper, we propose a solution that combines four technologies to address these challenges: Attribute-Based Encryption for data access control, blockchain for data integrity and non-repudiation, Hardware Security Modules for authenticity, and the Interplanetary File System for data scalability. We also use OpenID for dynamic client identification and propose a new method for user revocation in Attribute-Based Encryption. Our evaluation shows that the solution can scale up to 2,000,000 clients while maintaining all security guarantees.

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