Artykuły w czasopismach: „Hacking network”

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Prasanth, A., P. Sankar Ganesh i S. P. Raja Gopalan. "Data Prevention from Network Hacking". International Journal of Trend in Scientific Research and Development Volume-2, Issue-3 (30.04.2018): 807–11. http://dx.doi.org/10.31142/ijtsrd11035.

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Ul Haq, Hafiz Burhan, Muhammad Zulkifl Hassan, Muhammad Zunnurain Hussain, Rabia Aslam Khan, Sabreena Nawaz, Hassan Raza Khokhar i Mahnoor Arshad. "The Impacts of Ethical Hacking and its Security Mechanisms". Pakistan Journal of Engineering and Technology 5, nr 4 (29.12.2022): 29–35. http://dx.doi.org/10.51846/vol5iss4pp29-35.

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Hacking is a typical method for breaching personal and confidential information. As a result, hacking is also known as infiltration. Intrusions, on the other hand, were not always recognized as theft and were employed for productive purposes. A person or corporation that does ethical hacking and receives incentives from a network or system owner for testing can enter an apparatus (system or network) to locate, repair, and expose network flaws. Most ethical hackers, also known as black hat hackers, test systems using different approaches, methodologies, and tools. Because today's life is lived in a digital world, we need to protect our privacy from cyber-attacks. The proposed paper discussed ethical hacking and its ramifications, in which black hackers "hack" networks. The proposed research emphasizes ethical hacking tactics. This research also examines the impact of ethical hacking on business, education, health, society, the workplace, technology, sensitive information, and human life. Finally, a brief survey based on certain questions is better to grasp the public's understanding of ethical hacking. In summary, this research offers the user fascinating and helpful information when working on ethical hacking.

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Mohamad, Ani Munirah, Zaiton Hamin, Mohd Zakhiri Md Nor i Nurhazman Abdul Aziz. "SELECTED THEORIES ON CRIMINALISATION OF HACKING". International Journal of Law, Government and Communication 6, nr 22 (10.03.2021): 168–78. http://dx.doi.org/10.35631/ijlgc.6220016.

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Hacking or unauthorised access is criminalised in many jurisdictions, including Malaysia, Singapore, the United Kingdom, Hong Kong, and a few other countries. Hacking is the act of gaining access through the computer system or network without proper authority or exceeding the original authority given to him. Many commentators and researchers have reported on the conceptual and legal aspects of hacking. However, hacking's theoretical, conceptual, and legal aspects have remained under-researched. Therefore, this paper's primary objective is to outline the various theories, which could inform the criminalisation of hacking. The theories of routine activities, deterrence theory, social learning and self-control, general strain theory, and deviant subcultures are deliberated in this paper alongside illustrations within the context of hacking. This paper will shed light on the body of literature and contribute to a better understanding of hacking criminalisation from various theories discussed in this paper. Future research should be directed to provide empirical evidence of applying the theory to hacking criminalisation.

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Hancock, Bill. "Using network hacking techniques to disrupt military operational networks". Network Security 1998, nr 8 (sierpień 1998): 13–17. http://dx.doi.org/10.1016/s1353-4858(98)80075-5.

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Osagie, M. S. U., i Amenze Joy Osagie. "A Bit of Hacking Techniques for Vulnerable Subdomain". Journal of Advances in Computing, Communications and Information Technology 1 (25.04.2021): 1–7. http://dx.doi.org/10.37121/jaccit.v1.133.

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Hacking as it is popularly called is an official phrase for unauthorised access to a network/data. However, there are different methods used in gaining access to a designated network; hence, this paper explained a few hacker’s intent using classified commercially available tools and techniques to expose the vulnerability of data and applications within networks. It also explained few simple ways of gaining access to a network without really having the key technical ability.

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Schneier, B. "Hacking the business climate for network security". Computer 37, nr 4 (kwiecień 2004): 87–89. http://dx.doi.org/10.1109/mc.2004.1297316.

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García-Cobo, Iván. "Quantum Network Intelligent Management System". Optics 3, nr 4 (15.11.2022): 430–37. http://dx.doi.org/10.3390/opt3040036.

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Quantum network materializes the paradigm change caused by the depletion of classical computation. Quantum networks have been built gathering reliable quantum repeaters connected by optical fiber networks. The need to build robust and resilient networks against hacking attacks is fundamental in the design of the future quantum Internet, detecting structural security as the major issue in the current development of the technology. A network management method is proposed to achieve its real-time adaptation and to protect itself against sabotage or accidents that render part of the network or its nodes useless.

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Botha, Martin, i Rossouw von Solms. "The utilization of trend analysis in the effective monitoring of information security. Part 2: the model". Information Management & Computer Security 10, nr 1 (1.03.2002): 5–11. http://dx.doi.org/10.1108/09685220210417454.

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A survey recently completed by the Computer Security Institute (CSI) and the Federal Bureau of Investigation (FBI) revealed that corporations, banks, and governments all face a growing threat from computer crime, and in particular computer hacking. Computer hacking activities caused well over US$100 million in losses last year in the USA and the trend toward professional computer crime, such as computer hacking, is on the rise. Different methods are currently used to control the computer crime problem, for example, by controling access to and from a network by implementing a firewall. As the survey highlighted, most of these methods are insufficient. New means and ways which will minimise and control the hacking problem must therefore continuously be researched and defined. Proposes a method, using trend analysis, that could be utilized to minimise and control the hacking problem in an organisation.

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Hyunhee Park, Hyunhee Park. "Edge Based Lightweight Authentication Architecture Using Deep Learning for Vehicular Networks". 網際網路技術學刊 23, nr 1 (styczeń 2022): 195–202. http://dx.doi.org/10.53106/160792642022012301020.

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When vehicles are connected to the Internet through vehicle-to-everything (V2X) systems, they are exposed to diverse attacks and threats through the network connections. Vehicle-hacking attacks in the road can significantly affect driver safety. However, it is difficult to detect hacking attacks because vehicles not only have high mobility and unreliable link conditions, but they also use broadcast-based wireless communication. To this end, V2X systems need a simple but a powerful authentication procedure on the road. Therefore, this paper proposes an edge based lightweight authentication architecture using a deep learning algorithm for road safety applications in vehicle networks. The proposed lightweight authentication architecture enables vehicles that are physically separated to form a vehicular cloud in which vehicle-to-vehicle communications can be secured. In addition, an edge-based cloud data center performs deep learning algorithms to detect car hacking attempts, and then delivers the detection results to a vehicular cloud. Extensive simulations demonstrate that the proposed authentication architecture significantly enhanced the security level. The proposed authentication architecture has 94.51 to 99.8% F1-score results depending on the number of vehicles in the intrusion detection system using control area network traffic.

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Ellis, Tom, Xiao Wang i James J. Collins. "Gene Regulation: Hacking the Network on a Sugar High". Molecular Cell 30, nr 1 (kwiecień 2008): 1–2. http://dx.doi.org/10.1016/j.molcel.2008.03.005.

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Cuartielles Ruiz, David, i César García Sáez. "From Hacking to Making". Digital Culture & Society 6, nr 1 (1.12.2020): 85–106. http://dx.doi.org/10.14361/dcs-2020-0105.

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Abstract This article explores the history of contemporary Spanish Do-It- Yourself (DIY) spaces (hacklabs, hackerspaces, fab labs, makerspaces and after-school academies) and the growth of each type since the 1990s. The development of these types of spaces is reflected against the commodification and commoditisation of DIY in Spain. The article argues that the removal of the political layer of the early Spanish DIY techno-tactical movements allowed a higher degree of dissemination within society in general, while reducing the emancipatory potential of these new spaces. However, the analysis of the degree of commodification and commoditisation of types of spaces in relation to the amount of spaces per type shows an anomaly for makerspaces. The authors reflect upon this anomaly and whether a data set enlargement could correct it. For their analysis, the authors constructed a data set of events of the Spanish DIY history through the design of an ad hoc mixed method. Tracing events and spaces could not be done in a simple way due to the long time span of the study: older spaces existed in the pre-social network days, and new ones exist only in dedicated platforms for niche communities of practice. This method of tracing events and spaces is another contribution of the article as it could be used to make similar causality analyses of historical data in other case studies.

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Черкасов, Александр Николаевич, i Алена Валерьевна Сивенко. "Development of a model for ensuring the security of a social network account based on a neural network algorithm". Вестник Адыгейского государственного университета, серия «Естественно-математические и технические науки», nr 2(281) (28.09.2021): 47–55. http://dx.doi.org/10.53598/2410-3225-2021-2-281-47-55.

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Проведен анализ текущей статистики взлома учетных записей в социальных сетях. Построена архитектура нейронной сети, позволяющая классифицировать учетные записи пользователей на «безопасные» и «в зоне риска». Разработано программное обеспечение, позволяющее оценить надежность учетной записи пользователя в социальной сети «ВКонтакте». An analysis is made of the current statistics of hacking accounts in social networks. The architecture of a neural network has been built, which makes it possible to classify user accounts into “safe” and “at risk”. Software has been developed to assess the reliability of a user's account on the “VKontakte” social network.

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Tikhonova, Sophia V. "Maurizio Ferraris' Theory of Documentality and Social Media: Media Hacking as Hacking of Cultural Memory". Galactica Media: Journal of Media Studies 4, nr 2 (27.06.2022): 84–101. http://dx.doi.org/10.46539/gmd.v4i2.262.

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The article deals with the methodological search for overcoming dualism in the understanding of cultural memory as a basic category of memory studies. This category implies a gap between the memory of living contemporaries and the "dead" memory of institutional narratives. However, the rebellion of living memory against repressive censored texts is a feature of mass industrial societies. The model of confrontation between generational memory and trans-generational memory, laid down by the works of M. Halbwachs and J. Assmann, loses its heuristic in the conditions of the dominance of digital media. The author suggests using the social ontology of M. Ferraris, known as the “theory of documentality”, to overcome this gap. The interpretation of sociogenesis as a result of the formation of social objects based on the recording procedure allows us to rethink the social function of the media. Cultural memory in the theory of Ferraris is equivalent to an array of documentary, differentiated by the ability to generate and maintain social objects into strong and weak. This approach turns out to be productive where the “great gaps” of communication have been overcome, where the social communication system provides wide access to all its types. Social media provides new memory formats by incorporating people and non-human algorithms into its networks. Creation of social memory objects no longer requires specialized institutions; “old”, pre-digital narratives of historical memory are hacked by users in media hacking processes, allowing them to appropriate, edit and inhabit the history of society in personal digital memory strategies. At the same time, the digital nature of new social objects ensures their involvement with each other through social network algorithms, regardless of their own ethical, aesthetic or axiological status.

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Lee, Se-Yul, i Yong-Soo Kim. "Design and Analysis of Probe Detection Systems for TCP Networks". Journal of Advanced Computational Intelligence and Intelligent Informatics 8, nr 4 (20.07.2004): 369–72. http://dx.doi.org/10.20965/jaciii.2004.p0369.

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Advanced computer network technology enables the connectivity of computers in an open network environment. Despite the growing numbers of security threats to networks, most intrusion detection identifies security attacks mainly by detecting misuse using a set of rules based on past hacking patterns. This pattern matching has a high rate of false positives and cannot detect new hacking patterns, making it vulnerable to previously unidentified attack patterns and variations in attack and increasing false negatives. Intrusion detection and prevention technologies are thus required. We propose a network-based intrusion detection model using fuzzy cognitive maps (FCM) that detects intrusion by Denial of Service (DoS) attack detection using packet analysis. A DoS attack typically appears as a Probe and Syn Flooding attack. Syn Flooding Preventer using Fuzzy cognitive maps (SPuF) model captures and analyzes packet information to detect Syn flooding attacks. Using the result of decision module analysis, which used FCM, the decision module measures the degree of danger of the DoS and trains the response module to deal with attacks. The result of simulation using the "KDD’99 Competition Data Set" for the SPuF model shows that Probe detection exceeded 97%.

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Aghila, R., K. Nagalakshmi, B. S. Roopan, S. Rajakrishnan i T. Anandaraj. "A Formal Analysis and Some Properties of Kerberos in Network Security". Asian Journal of Computer Science and Technology 1, nr 1 (5.05.2012): 6–10. http://dx.doi.org/10.51983/ajcst-2012.1.1.1697.

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Network is a chain, a weak link in that can break a system. Network plays a vital role in modern computer industry. Making secure network is more important because a lot of confidential transactions are performed over the network. In this world of universal electronic connectivity “Hackers” threaten the prosperity and productivity of individuals and corporations, to prevent that we introduce a new type of security with KERBEROS. This paper deals with networking in a most secured manner. In this advanced Hacking world network security seems to be more important and it plays a vital role in communication over networks. This is made possible by using the KERBEROS, the best way of implementing the network security.

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Pisarić, Milana. "The use of policeware to hack electronic evidence in Germany and the Netherlands". Nauka, bezbednost, policija 28, nr 1 (2023): 16–26. http://dx.doi.org/10.5937/nabepo28-43759.

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Hacking as manipulation of software, data, computer system or network without the knowledge and permission of the user constitutes an act of criminal offence. However, given that certain technological tendencies make it difficult/impossible to collect electronic evidence, the question arises as to whether the authorities responsible for detecting and proving criminal offenses should be authorized to hack, i.e. to conduct investigations in the digital environment in such a way that they would be authorized to exploit technical, systemic and human vulnerabilities within the IT system, without knowledge and permission of the user, in order to gain a remote access to protected system and conduct further actions. Although a state authorities' hacking with the aim of collecting electronic evidence carries immense risks for information security and human rights and freedoms with it, one cannot dispute that the deployment of such techniques might be useful in criminal investigations. However, the application of hacking technique would not per se violate the right to privacy and other guaranteed rights and freedoms, only as far as such interference is properly regulated. Hence, the legal framework should explicitly regulate the lawful hacking as a special investigative measure, especially the conditions that should be met and mechanisms that should be applied. As hacking for the purposes of criminal investigation may be performed through various techniques, this paper focuses on a hacking technique based on a malware, and its regulations in two countries with explicit provisions - Germany and the Netherlands.

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Chaudhary, Sachin, i Kanchan Chaudhary. "Distributed Honeypots System". International Journal of Advance Research and Innovation 1, nr 2 (2013): 5–11. http://dx.doi.org/10.51976/ijari.121302.

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Honeypot is a supplemented active defence system for network security. It traps attacks, records intrusion information about tools and activities of the hacking process, and prevents attacks outbound the compromised system. Integrated with other security solutions, Honeypot can solve many traditional dilemmas. It has emerged as a prominent technology that helps learn new hacking techniques from attackers and intruders. Honeypots can initiatively lure hackers to attack the internet, take the record of the ways and means of their invasion, and then analyze and study them.

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Kwon, Se-Hwan, i Dea-Woo Park. "Hacking and Security of Encrypted Access Points in Wireless Network". Journal of information and communication convergence engineering 10, nr 2 (30.06.2012): 156–61. http://dx.doi.org/10.6109/jicce.2012.10.2.156.

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WANG, Xue-rui, i Yong-qiang HE. "Security Management and Prevention on the Campus Network against Hacking". Journal of Information Security Research 10, nr 3 (1.09.2019): 87. http://dx.doi.org/10.6025/jisr/2019/10/3/87-91.

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Bang, Sang-Won, Byeong-Soo Jung i Sang-Cheol Lee. "Research on financial institutional network partition design for anti-hacking". Journal of Computer Virology and Hacking Techniques 13, nr 4 (29.04.2017): 257–63. http://dx.doi.org/10.1007/s11416-017-0297-3.

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Chun, Yangha. "Analysis of Cyber Threats in the Connection Section of the Control System and Countermeasures Required". Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, nr 6 (10.04.2021): 412–17. http://dx.doi.org/10.17762/turcomat.v12i6.1831.

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In the past, the general practice for the control system network that manages and controls industrial facilities such as electric power, gas, oil, water, chemicals, automobiles, etc. was to install and operate this as an independent system, but over time the practice has gradually shifted toward the use of an open and standardized system. Until recently, most industrial control systems consisted of an independent network, and the possibility of cyber threat infringement was very low. As information storage media such as laptops or USB are connected to the control system for maintenance or management purposes, the possibility of cyber infringement is increasing. When the use of the control system's operational information increases due to beingVinked with the internal business system network or the Internet, countermeasures against external cyber threats must be provided.This paper analyzes and organizes the cyber threat factors that exist in the linking section connected to the industrial control system and other networks, examining domestic and foreign incidents of hacking of control systems to identify the vulnerabilities and security measures for each scenario in the control system network linkage section. Through this analysis, a method is suggested for establishing a control network that secures both availability and security, which are important in the control system, as well as the safe relay system in the configuration of the linkage between the control network and the business network, while addressing the vulnerabilities in the structure due to long-term use of the control system.This study analyzes cyber threat factors and real-life examples of infringements with the aim of providing approaches that will ensure industrial control systems can be operated safely and the risk of cyber hacking threats that occur in connection with other networks can be managed, and suggesting cyber security measures for the control system connection sections.

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Ahmad, Bilal, Wang Jian i Zain Anwar Ali. "Role of Machine Learning and Data Mining in Internet Security: Standing State with Future Directions". Journal of Computer Networks and Communications 2018 (2.07.2018): 1–10. http://dx.doi.org/10.1155/2018/6383145.

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As time progresses with vast development of information technology, a large number of industries are more dependent on network connections for sensitive business trading and security matters. Communications and networks are highly vulnerable to threats because of increase in hacking. Personnel, governments, and armed classified networks are more exposed to difficulties, so the need of the hour is to install safety measures for network to prevent illegal modification, damage, or leakage of serious information. Intrusion detection, an important entity towards network security, has the ability to observe network activity as well as detect intrusions/attacks. This study highlights the developing research about the application of machine learning and data mining in Internet security. We provide background, enthusiasm, discussion of challenges, and recommendations for the application of ML/DM in the field of intrusion detection.

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S.Sowmiyasree and Dr.T.Ranganayaki. "Data Analytics Era: Survey of Analysis of Banking System by using Blockchain". International Journal for Modern Trends in Science and Technology 9, nr 01 (25.01.2023): 62–68. http://dx.doi.org/10.46501/ijmtst0901011.

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Blockchain is a decentralised, unchangeable ledger that records transactions in a network and is a distributed database. The blocks that hold the transactions' information are immutable and used to record them. The majority of programme participants review all of the community manual's activities twice. Data cannot be deleted once it has been input. Numerous sorts of information fraud can be avoided by keeping track of actions that are taken permanently, implicitly, and definitively. Since each transaction must be carried out by a team of miners, fraudulent transactions cannot exceed cumulative guarantees and guarantees. Hacking, hacking, and breach are all feasible with modest data storage and administration systems, but the widely used blockchain compliance mechanism prohibits this. Any good, service, or asset can be directed. fraud, theft of identities, and network or system failure.

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Mungekar, Abhishek, Yashraj Solanki i R. Swarnalatha. "Augmentation of a SCADA based firewall against foreign hacking devices". International Journal of Electrical and Computer Engineering (IJECE) 10, nr 2 (1.04.2020): 1359. http://dx.doi.org/10.11591/ijece.v10i2.pp1359-1366.

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An Industrial firewall is a system used to supervise and regulate traffic to and from a network for the purpose of securing appliances on a network. It analyzes the data passing through it to an already defined surveillance criteria or protocols, discarding data that does not meet the protocol’s requirements. In effect, it is a filter preventing undesirable network traffic and selectively limiting the type of transmission that occurs between a secured transmission line. In this research paper a SCADA based Firewall is implemented for protection of the data transmission to a PLC, against external hacking devices. This firewall is virtually exposed to several external hackers and the degree of vulnerability is carefully studied, in order to develop an ideal Firewall.

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Pisarić, Milana. "THE USE OF HACKING TECHNIQUES FOR THE PURPOSE OF CRIMINAL PROCEDURE". Journal of Criminology and Criminal Law 61, nr 1 (czerwiec 2023): 51–66. http://dx.doi.org/10.47152/rkkp.61.1.3.

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Since certain trends in information technologies significantly hinder criminal investigation, there is an evident need for the creation of an appropriate criminal procedure mechanism to overcome these obstacles. One of the options is to enable the law enforcement agencies to use hacking techniques in order to gain access to protected computer systems, networks and data, even remotely, in order to identify suspects, to monitor their activities and communications, and to collect evidence. In this paper the author is considering the possibilities, advantages and risks of using hacking techniques for the purposes of criminal proceedings. After pointing out the risks of malware use by the competent authorities, the normative framework for overcoming those risks was considered through regulating the authorized access to a protected computer system or network, as a special investigative action, so the data obtained through such actions could be used as evidence in the court of law.

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Kim, Seong-Kyu. "Automotive Vulnerability Analysis for Deep Learning Blockchain Consensus Algorithm". Electronics 11, nr 1 (30.12.2021): 119. http://dx.doi.org/10.3390/electronics11010119.

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In this study, future cars are attempting self-driving around the world. However, hacking, such as ECUs in automobiles, creates problems that are directly connected to human life. Therefore, this study wrote a paper that detects anomalies in such cars by field. As a related study, the study investigated the vulnerabilities of the automobile security committee and automobile security standards and investigated the detection of abnormalities in the hacking of geo-train cars using artificial intelligence’s LSTM and blockchain consensus algorithm. In addition, in automobile security, an algorithm was studied to predict normal and abnormal values using LSTM-based anomaly detection techniques on the premise that automobile communication networks are largely divided into internal and external networks. In the methodology, LSTM’s pure propagation malicious code detection technique was used, and it worked with an artificial intelligence consensus algorithm to increase security. In addition, Unity ML conducted an experiment by constructing a virtual environment using the Beta version. The LSTM blockchain consensus node network was composed of 50,000 processes to compare performance. For the first time, 100 Grouped Tx, 500 Channels were tested for performance. For the first time, the malicious code detection rate of the existing system was verified. Accelerator, Multichannel, Sharding, Raiden, Plasma, and Trubit values were verified, and values of approximately 15,000 to 50,000 were obtained. In this paper, we studied to become a paper of great significance on hacking that threatens human life with the development of self-driving cars in the future.

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Bezmaternykh, P. V., D. A. Ilin i D. P. Nikolaev. "U-Net-bin: hacking the document image binarization contest". Computer Optics 43, nr 5 (październik 2019): 825–32. http://dx.doi.org/10.18287/2412-6179-2019-43-5-825-832.

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Image binarization is still a challenging task in a variety of applications. In particular, Document Image Binarization Contest (DIBCO) is organized regularly to track the state-of-the-art techniques for the historical document binarization. In this work we present a binarization method that was ranked first in the DIBCO`17 contest. It is a convolutional neural network (CNN) based method which uses U-Net architecture, originally designed for biomedical image segmentation. We describe our approach to training data preparation and contest ground truth examination and provide multiple insights on its construction (so called hacking). It led to more accurate historical document binarization problem statement with respect to the challenges one could face in the open access datasets. A docker container with the final network along with all the supplementary data we used in the training process has been published on Github.

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Rani, S. Vijaya, i G. N. K. Suresh Babu. "Optimizing Error Rate in Intrusion Detection System Using Artificial Neural Network Algorithm". International Journal of Emerging Research in Management and Technology 6, nr 9 (24.06.2018): 152. http://dx.doi.org/10.23956/ijermt.v6i9.102.

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The illegal hackers penetrate the servers and networks of corporate and financial institutions to gain money and extract vital information. The hacking varies from one computing system to many system. They gain access by sending malicious packets in the network through virus, worms, Trojan horses etc. The hackers scan a network through various tools and collect information of network and host. Hence it is very much essential to detect the attacks as they enter into a network. The methods available for intrusion detection are Naive Bayes, Decision tree, Support Vector Machine, K-Nearest Neighbor, Artificial Neural Networks. A neural network consists of processing units in complex manner and able to store information and make it functional for use. It acts like human brain and takes knowledge from the environment through training and learning process. Many algorithms are available for learning process This work carry out research on analysis of malicious packets and predicting the error rate in detection of injured packets through artificial neural network algorithms.

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KOMBATE, Yendoubé, Pélagie HOUNGUE i Samuel OUYA. "A bibliometric method for analyzing IoT hacking solutions in network services". Procedia Computer Science 203 (2022): 141–48. http://dx.doi.org/10.1016/j.procs.2022.07.020.

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Shea, J. J. "Hacking Exposed-Network Security Secrets & Solutions, 4th Ed. [Book Review]". IEEE Electrical Insulation Magazine 19, nr 5 (wrzesień 2003): 73–74. http://dx.doi.org/10.1109/mei.2003.1238725.

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Arévalo Ortega, Yamir Alexander, Sonia Rocio Corredor Vargas i Gustavo Adolfo Higuera Castro. "Forensic analysis with hacking tools on android devices". Visión electrónica 13, nr 1 (31.01.2019): 162–77. http://dx.doi.org/10.14483/22484728.14405.

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Currently, the use of mobile terminals is becoming a necessity for a high number of people around the world which has driven the development of devices with Android operating system; In addition to this, the same indiscriminate access to resources of internet and weak local and international regulations on the use, they have become vulnerable to attacks on the network - injection of malware, ransomware-, among many others. Therefore, this article reviews the hacking tools for the forensic investigation of mobile terminals, proposing from the documentary research a forensic information acquisition model to determine tangible and significant evidences as a probative material.

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Bartolacci, Michael R., i Stanko Dimitrov. "Promoting Resiliency in Emergency Communication Networks". International Journal of Information Systems for Crisis Response and Management 9, nr 1 (styczeń 2017): 1–10. http://dx.doi.org/10.4018/ijiscram.2017010101.

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Police, fire, and emergency personnel rely on wireless networks to serve the public. Whether it is during a natural disaster, or just an ordinary calendar day, wireless nodes of varying types form the infrastructure that local, regional, and even national scale agencies use to communicate while keeping the population served safe and secure. In this article, Michael R. Bartolacci and Stanko Dimitrov present a network interdiction modeling approach that can be utilized for analyzing vulnerabilities in public service wireless networks; subject to hacking, terrorism, or destruction from natural disasters. They develop a case study for wireless networks utilized by the sheriff's department of Miami-Dade County in Florida in the United States. Finally, the authors' modeling approach—given theoretical budgets for the “hardening” of wireless network nodes and for would-be destroyers of such nodes—highlights parts of the network where further investment may prevent damage and loss of capacity.

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Sati, Vrinda, i Raja Muthalagu. "Analysis on Hacking the Secured Air-Gapped Computer and Possible Solution". Cybernetics and Information Technologies 23, nr 2 (1.06.2023): 124–36. http://dx.doi.org/10.2478/cait-2023-0017.

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Abstract The world today runs on data, every minuscule task to the large one requires data. All the data is stored in the various technologies that we use. And to keep data safe, air gaps are introduced. Air gaps are a network security measure where secure computer networks are physically isolated from unsecured networks. Yet, different methods to hack the air gap have come forth. The paper analyzes the problem of hacking an air gap via screen brightness modulations. The proposed solution is a software program used to alert the user of a change in the brightness level of the screen. The concept of Windows Management Instrumentation (WMI) has been used to put forth the software. Applied to an air-gapped computer, the program displays an alert box immediately, as the screen brightness changes. The solution is an easy and efficient way to counter the attack. The program can be further implemented in different testing environments and the WMI concept can be applied to various other cyber hacks.

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Lin, Hsiao-Chung, Ping Wang, Kuo-Ming Chao, Wen-Hui Lin i Jia-Hong Chen. "Using Deep Learning Networks to Identify Cyber Attacks on Intrusion Detection for In-Vehicle Networks". Electronics 11, nr 14 (12.07.2022): 2180. http://dx.doi.org/10.3390/electronics11142180.

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With rapid advancements in in-vehicle network (IVN) technology, the demand for multiple advanced functions and networking in electric vehicles (EVs) has recently increased. To enable various intelligent functions, the electrical system of existing vehicles incorporates a controller area network (CAN) bus system that enables communication among electrical control units (ECUs). In practice, traditional network-based intrusion detection systems (NIDSs) cannot easily identify threats to the CAN bus system. Therefore, it is necessary to develop a new type of NIDS—namely, on-the-move Intrusion Detection System (OMIDS)—to categorise these threats. Accordingly, this paper proposes an intrusion detection model for IVNs, based on the VGG16 classifier deep learning model, to learn attack behaviour characteristics and classify threats. The experimental dataset was provided by the Hacking and Countermeasure Research Lab (HCRL) to validate classification performance for denial of service (DoS), fuzzy attacks, spoofing gear, and RPM in vehicle communications. The proposed classifier’s performance was compared with that of the XBoost ensemble learning scheme to identify threats from in-vehicle networks. In particular, the test cases can detect anomalies in terms of accuracy, precision, recall, and F1-score to ensure detection accuracy and identify false alarm threats. The experimental results show that the classification accuracy of the dataset for HCRL Car-Hacking by the VGG16 and XBoost classifiers (n = 50) reached 97.8241% and 99.9995% for the 5-subcategory classification results on the testing data, respectively.

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Zhia Sheng, Dalian Wu, Isredza Rahmi A. Hamid i Hannani Aman. "Multilevel Authentication for Social Network". JOIV : International Journal on Informatics Visualization 2, nr 3-2 (6.06.2018): 220. http://dx.doi.org/10.30630/joiv.2.3-2.146.

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Nowadays, social network plays a vital role in communication. Normally user used social networks in daily activities. However, this left all online users susceptible to misuse and abuse. Recently, there has been a remarkable growth in number of hacking as well. Once the computer is online, anyone can have access to the network. Therefore, we proposed a secure social network site called SocialBook where users can post status, photos and connect with friends. This system is developed using PHP programming language and Iterative and Incremental Development methodology. The purpose of developing this system is to solve unsecured login accounts and lack of user authentication problem. This system applies the secret question procedure when the user wants to change their account password. Moreover, SocialBook use idle session timeout mechanism for additional security. When the user is idle for ten minutes, they will be logged out automatically. So, the user will be less worry about their account from being hacked and the identity impersonation by unauthorized user.

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Kurniawan, Ade, Yuichi Ohsita i Masayuki Murata. "Experiments on Adversarial Examples for Deep Learning Model Using Multimodal Sensors". Sensors 22, nr 22 (9.11.2022): 8642. http://dx.doi.org/10.3390/s22228642.

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Recently, artificial intelligence (AI) based on IoT sensors has been widely used, which has increased the risk of attacks targeting AI. Adversarial examples are among the most serious types of attacks in which the attacker designs inputs that can cause the machine learning system to generate incorrect outputs. Considering the architecture using multiple sensor devices, hacking even a few sensors can create a significant risk; an attacker can attack the machine learning model through the hacked sensors. Some studies demonstrated the possibility of adversarial examples on the deep neural network (DNN) model based on IoT sensors, but it was assumed that an attacker must access all features. The impact of hacking only a few sensors has not been discussed thus far. Therefore, in this study, we discuss the possibility of attacks on DNN models by hacking only a small number of sensors. In this scenario, the attacker first hacks few sensors in the system, obtains the values of the hacked sensors, and changes them to manipulate the system, but the attacker cannot obtain and change the values of the other sensors. We perform experiments using the human activity recognition model with three sensor devices attached to the chest, wrist, and ankle of a user, and demonstrate that attacks are possible by hacking a small number of sensors.

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Luo, Anlun. "Intrusion Detection System for Internet of Vehicles Based on Ensemble Learning and CNN". Journal of Physics: Conference Series 2414, nr 1 (1.12.2022): 012014. http://dx.doi.org/10.1088/1742-6596/2414/1/012014.

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Abstract With the combination of network and automotive technology, more and more modern cars are controlled based on electronic control units (ECUs). And multiple ECUs in modern cars are interconnected and cooperate through the in-vehicle network. But such in-vehicle networks do not consider potential security issues, which might lead to property damage and life threat. An intrusion Detection System (IDS) is a method to detect anomalies and warn about network intrusions. In this study, an IDS model based on Convolutional Neural Networks (CNNs) and ensemble learning is proposed. Meanwhile, to further improve the capability of the proposed IDS model, the structure of some CNN basic models is modified. Finally, the proposed model is validated on a representative standard Internet of Vehicles (IoV) dataset Car-Hacking Dataset. In the experiment, the proposed model achieves 100% accuracy and fl-score, and the detection time is from 1.0ms to 2.8ms, which demonstrates that the proposed IDS model detects the effectiveness of network intrusions.

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Ji, Hong. "Research on the Protection Strategy of Network Security". Advanced Materials Research 703 (czerwiec 2013): 236–39. http://dx.doi.org/10.4028/www.scientific.net/amr.703.236.

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The global information has become the human development trend with the development of network technology. People enjoy the convenience brought by the network technology and confront many network security issues. Because the network attack behavior has concealment, complexity and permeability, the network security issues become increasingly prominent and the network security protection become more difficult. Based on the analysis of the threatening factors to the network security, such as hacking, computer viruses, computer system vulnerabilities, security issues of the network protocol, weak authentication and logic bombs, the firewall technology, intrusion detection technology, access control technology and computer virus protection technology are proposed to ensure safe and stable operation and use of network.

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Hadi, Teeb Hussein. "Types of Attacks in Wireless Communication Networks". Webology 19, nr 1 (20.01.2022): 718–28. http://dx.doi.org/10.14704/web/v19i1/web19051.

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One of the most important types that used to transfer data between nodes without using wires is a “wireless communication network”, where the transmission of data is censored remotely by using electromagnetic waves such as radio waves that usually implemented in the physical layer of the network. Continuous improvements in wireless network technology have reduced the security and speed differences between types of networks (wired and wireless), but in turn, increased security threats to wirelessly transmitted data. Wireless networks are weak in terms of "privacy protection" because anyone who is within the coverage area of a wireless network can attempt to break into that network. Hacking incidents have been reported frequently in places with shared free networks, and it has been observed that the places of open distributed networks of the Internet are most at risk of complete penetration of your phone or PC data. To solve this problem, several programs have been developed that provide protection for wireless networks that differ in terms of security. Some of them did not provide sufficient protection for wireless networks, such as Wired Equivalent Privacy (WEP), and others made progress in preventing intrusions compared to their predecessors, such as Wi-Fi Protected Access (WPA).

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Andi, Hari Krishnan. "Estimating the Role of Blockchain, Deep Learning and Cryptography algorithms in Cloud Security". Journal of Trends in Computer Science and Smart Technology 3, nr 4 (19.05.2022): 305–13. http://dx.doi.org/10.36548/jtcsst.2021.4.006.

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Cloud network has become very popular in recent days due to its accessibility merits. The data stored in the cloud environment are accessible by the clients from any location. A reliable shielding approach will protect the data stored in the cloud from the hackers and malwares. Blockchain is one of the recent technologies implemented to the cloud network for storing the location of the saved data in an encrypted ledger format. This saves the stored data location without exploring it to the hacker’s algorithm. Hence the hacking algorithm fails by not knowing the location to be targeted. Deep learning is an advanced technique developed to act like that of the human neurological analysis on several problems. Implementation of deep learning algorithm to the cloud security module identifies the movement of malware and spywares in the cloud storage. Similarly the cryptography is an old technique structured to hide the information with a cover data or cover image. It allows the hacking algorithm to extract only the useless data. This paper reviews the recent advancements in the cloud security with blockchain, deep learning and cryptographic models.

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Громов, Юрий Юрьевич, Павел Игоревич Карасев i Виктор Владимирович Кулешов. "ANALYSIS OF MODERN ACCESS POINTS FOR ENTERPRISE WIRELESS CHANNELS". ИНФОРМАЦИЯ И БЕЗОПАСНОСТЬ, nr 4(-) (15.12.2021): 587–92. http://dx.doi.org/10.36622/vstu.2021.24.4.011.

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В статье дается характеристика беспроводных сетей, имеющих значение для автоматизации производства, и условия для их применения. Рассмотрено применение проводной сети Ethernet, поскольку беспроводная сеть можно с легкостью в нее интегрироваться. Проведен анализ таких распространенных в автоматизации предприятий типов стандартов связи, как ZigBee и Wi-Fi. Уделено внимание проблеме взаимодействия узлов в проводных и беспроводных сетях и возможности ее решения с использованием технологии коллективного доступа с опознаванием несущей и обнаружением конфликтов. Определено, что точки доступа являются устройствами обладающими операционными системами, в которых содержится большое количество ошибок, чем могут воспользоваться злоумышленники. Рассмотрены основные причины взлома на примере Wi-Fi и охарактеризованы методы взлома беспроводной точки доступа. Указаны способы, которые могут применяться для защиты беспроводной точки доступа можно использовать следующие способы. Также проведен анализ технологий, которые могут использоваться для того, чтобы защитить корпоративные сети. The article describes the characteristics of wireless networks that are important for the automation of production, and the conditions for their use. The application of a wired Ethernet network is considered, since a wireless network can be easily integrated into it. The analysis of such types of communication standards common in enterprise automation as ZigBee and Wi-Fi is carried out. Attention is paid to the problem of interaction of nodes in wired and wireless networks and the possibility of solving it using the technology of collective access with carrier identification and conflict detection. It is determined that access points are devices with operating systems that contain a large number of errors, which can be used by attackers. The main reasons for hacking on the example of Wi-Fi are considered and methods of hacking a wireless access point are described. The methods that can be used to protect the wireless access point are indicated, you can use the following methods. The analysis of technologies that can be used to protect corporate networks is also carried out.

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Ibrahim, Mohanad R., i Karam Thanoon. "Quasar Remote Access Trojan feature extraction depending on Ethical Hacking". Technium: Romanian Journal of Applied Sciences and Technology 4, nr 1 (27.01.2022): 58–75. http://dx.doi.org/10.47577/technium.v4i1.5831.

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These days, computer Trojans had become in the top of the most dangerous types of malwares threats. There is a lot of remote access tools that have ability to manage and apply many features remotely. Quasar Trojan is one of the most uses for Remote Access Trojan (RAT). The researchers apply Quasar on real environment in lab (ethically and for education purposes) and this paper presents the capabilities of Trojans. This paper will present some of Quasar features by extract most important features also presents how to access remotely by using no-IP address (DUC) with other tools of applying access of internal network ethically.

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Shmaryahu, Dorin, Guy Shani, Joerg Hoffmann i Marcel Steinmetz. "Simulated Penetration Testing as Contingent Planning". Proceedings of the International Conference on Automated Planning and Scheduling 28 (15.06.2018): 241–49. http://dx.doi.org/10.1609/icaps.v28i1.13902.

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In penetration testing (pentesting), network administrators attack their own network to identify and fix vulnerabilities. Planning-based simulated pentesting can achieve much higher testing coverage than manual pentesting. A key challenge is for the attack planning to imitate human hackers as faithfully as possible. POMDP models have been proposed to this end, yet they are computationally very hard, and it is unclear how to acquire the models in practice. At the other extreme, classical planning models are scalable and simple to obtain, yet completely ignore the incomplete knowledge characteristic of hacking. We propose contingent planning as a new middle ground, feasible in both computation burden and model acquisition effort while allowing for a representation of incomplete knowledge. We design the model, show how to adapt available solvers, and show how to acquire the model from real network scans in practice. We experiment on real networks and show that our approach scales to practical input sizes.

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Tiwari, Shamik. "An Ensemble Deep Neural Network Model for Onion-Routed Traffic Detection to Boost Cloud Security". International Journal of Grid and High Performance Computing 13, nr 1 (styczeń 2021): 1–17. http://dx.doi.org/10.4018/ijghpc.2021010101.

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Anonymous network communication using onion routing networks such as Tor are used to guard the privacy of sender by encrypting all messages in the overlapped network. These days most of the onion routed communications are not only used for decent cause but also cyber offenders are ill-using onion routings for scanning the ports, hacking, exfiltration of theft data, and other types of online frauds. These cyber-crime attempts are very vulnerable for cloud security. Deep learning is highly effective machine learning method for prediction and classification. Ensembling multiple models is an influential approach to increase the efficiency of learning models. In this work, an ensemble deep learning-based classification model is proposed to detect communication through Tor and non-Tor network. Three different deep learning models are combined to achieve the ensemble model. The proposed model is also compared with other machine learning models. Classification results shows the superiority of the proposed model than other models.

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Smys, S. "Recent Security Features of 5G Protocol for Real Time Network Domain – An Overview". Journal of ISMAC 3, nr 4 (12.04.2022): 314–25. http://dx.doi.org/10.36548/jismac.2021.4.003.

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Numerous mission-critical applications in the field of information technology will rely on fifth generation (5G) networks in the future. The 5G is projected to bring new technological improvements and innovation. Software-Defined Networking (SDN) is the present backbone of 5G. Because of the specific needs of each application that may be met by network slicing, 5G can provide this feature. In comparison to 4G Long-Term Evolution (LTE) and preceded generations, 5G is more adaptable and scalable. However, considerable advances in 5G cyber security are required to minimise the rising threats of hacking. Both the network and the devices linked to 5G are subjected to security problems. 5G communication networks' weaknesses may create many dangerous unknown attacks. However, it depends on the 5G privacy and security key protocol. In addition, several dangerous attacks may be combined to provide a wide range of attack options for hackers. For the 5G communication network, this article provides a complete framework for security analysis. The findings of this study might lead to unique 5G communication exploits. Moreover, artificial intelligence learning has been recently used to create and analyse attack graphs for software-defined and virtualized 5G communication networks.

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Smys, S. "Recent Security Features of 5G Protocol for Real Time Network Domain – An Overview". Journal of ISMAC 3, nr 4 (12.04.2022): 314–25. http://dx.doi.org/10.36548/10.36548/jismac.2021.4.003.

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Numerous mission-critical applications in the field of information technology will rely on fifth generation (5G) networks in the future. The 5G is projected to bring new technological improvements and innovation. Software-Defined Networking (SDN) is the present backbone of 5G. Because of the specific needs of each application that may be met by network slicing, 5G can provide this feature. In comparison to 4G Long-Term Evolution (LTE) and preceded generations, 5G is more adaptable and scalable. However, considerable advances in 5G cyber security are required to minimise the rising threats of hacking. Both the network and the devices linked to 5G are subjected to security problems. 5G communication networks' weaknesses may create many dangerous unknown attacks. However, it depends on the 5G privacy and security key protocol. In addition, several dangerous attacks may be combined to provide a wide range of attack options for hackers. For the 5G communication network, this article provides a complete framework for security analysis. The findings of this study might lead to unique 5G communication exploits. Moreover, artificial intelligence learning has been recently used to create and analyse attack graphs for software-defined and virtualized 5G communication networks.

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Druzin, Bryan. "Can the Liberal Order be Sustained? Nations, Network Effects, and the Erosion of Global Institutions". Michigan Journal of International Law, nr 42.1 (2021): 1. http://dx.doi.org/10.36642/mjil.42.1.can.

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A growing retreat from multilateralism is threatening to upend the institutions that underpin the liberal international order. This article applies network theory to this crisis in global governance, arguing that policymakers can strengthen these institutions by leveraging network effect pressures. Network effects arise when networks of actors—say language speakers or users of a social media platform—interact and the value one user derives from the network increases as other users join the network (e.g., the more people who speak your language, the more useful it is because there are more people with whom you can communicate). Crucially, network effect pressures produce what is called ‘lock-in’—a situation in which actors are unable to exit the network without incurring high costs and as a result become locked into the network. For example, because of their powerful network effect pressures, users of Facebook and the English language cannot easily exit these networks. International organizations such as the UN, the WTO, the IMF, etc., are networks of sovereign states that likewise produce network effect pressures. As such, intensifying their network effect pressure can lock countries more firmly into these institutions. To that end, this article proposes a suite of strategies policymakers may use to manipulate the network effect pressures generated by international organizations to strengthen these institutions and the multilateral treaties that establish them—an approach the article calls treaty hacking. The article offers a toolkit from which policymakers can draw to bolster the liberal order in the face of growing global instability and change.

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Abdullah, Mokhaled N., Ihab A. Satam, Raid W. Daoud, Suhail N. Shihab i Haider A. Kamel. "Design and implement a self-managed computer network for electronic exams and sharing". Indonesian Journal of Electrical Engineering and Computer Science 19, nr 1 (1.07.2020): 466. http://dx.doi.org/10.11591/ijeecs.v19.i1.pp466-475.

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To implement electronic exams and material resources sharing (which is usually limited), an operating base is must be available for trading information and correspondence management. In this paper, self-managed computer networks, no server was designed. This network aims to share information and correspondence management between the laboratory`s computers. A specific software called Packet tracer used for designing and simulating the network, also for choosing the right medium and install the IP address so that a maximum of data flowing with minimum time and no data loss can be achieved. A class-C IP address was selected since it is the famous class and it doesn`t need any special equipment. Also it has a wide range of of computers in case of expanding the network. We didn`t use a wireless medium to protect the network from hacking. The network was based on an Ethernet medium and a star-connection between the computers with an average signal distributer. An excellent result was achieved after testing the network with a low error percentage, as shown in the result section of this paper.

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Xu, Song, i Ping He. "Protection System of Cooperative Network Based on Artificial Immune Theory". Advanced Materials Research 108-111 (maj 2010): 1360–65. http://dx.doi.org/10.4028/www.scientific.net/amr.108-111.1360.

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The paper proposes a network security monitoring protection model with synergetic mechanism based on the basic principle of human immune system and the state quo of network hacking inspection research and the analysis and appraisal on the original artificial immune model. This model proposes human-computer interaction disaster warning system based on computer dangerous operation and the advantage of agent technology and proposes free-state anti-virus technology based on the human body apoptotic cells. The test results show that the methods proposed in this thesis remedy the illegal program escaped from monitoring security scanning and the system security hidden danger caused manually and at last proposes the development trend of the future artificial immunity in computer protection field.

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Youn, Jaepil, Kookjin Kim, Daeyoung Kang, Jaeil Lee, Moosung Park i Dongkyoo Shin. "Research on Cyber ISR Visualization Method Based on BGP Archive Data through Hacking Case Analysis of North Korean Cyber-Attack Groups". Electronics 11, nr 24 (12.12.2022): 4142. http://dx.doi.org/10.3390/electronics11244142.

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North Korean cyber-attack groups such as Kimsuky, Lazarus, Andariel, and Venus 121 continue to attempt spear-phishing APT attacks that exploit social issues, including COVID-19. Thus, along with the worldwide pandemic of COVID-19, related threats also persist in cyberspace. In January 2022, a hacking attack, presumed to be Kimsuky, a North Korean cyber-attack group, intending to steal research data related to COVID-19. The problem is that the activities of cyber-attack groups are continuously increasing, and it is difficult to accurately identify cyber-attack groups and attack origins only with limited analysis information. To solve this problem, it is necessary to expand the scope of data analysis by using BGP archive data. It is necessary to combine infrastructure and network information to draw correlations and to be able to classify infrastructure by attack group very accurately. Network-based infrastructure analysis is required in the fragmentary host area, such as malware or system logs. This paper studied cyber ISR and BGP and a case study of cyber ISR visualization for situational awareness, hacking trends of North Korean cyber-attack groups, and cyber-attack tracking. Through related research, we estimated the origin of the attack by analyzing hacking cases through cyber intelligence-based profiling techniques and correlation analysis using BGP archive data. Based on the analysis results, we propose an implementation of the cyber ISR visualization method based on BGP archive data. Future research will include a connection with research on a cyber command-and-control system, a study on the cyber battlefield area, cyber ISR, and a traceback visualization model for the origin of the attack. The final R&D goal is to develop an AI-based cyber-attack group automatic identification and attack-origin tracking platform by analyzing cyber-attack behavior and infrastructure lifecycle.

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