Articles de revues : « Multimedia forensic »

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Okan, Emmanuel Tettey. « Forensic Analysis on Streaming Multimedia ». Advances in Multidisciplinary and scientific Research Journal Publication 1, n^o 1 (26 juillet 2022) : 221–26. http://dx.doi.org/10.22624/aims/crp-bk3-p36.

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Since the advent of technology and digitalization of multimedia, there has been a massive increase in cybercrime. During streaming, with the availability of a network or internet source, multimedia; audio and visual can easily be accessed whiles being aired live. This technology dates as far back as 1990s. Similar to still videos and images, the user is able to download, pause, reverse or forward the show. The ability to stream multimedia has made it easier for users to partake or retrieve multimedia from the comfort of their homes, offices or personal spaces without necessarily being present. However, there are several challenges that affect the functionality of this technology, slow network connection and cybercrime. The issue of slow network may easily be handled by network providers, but cybercrimes has become rampant over the years. These attackers, also known as cyber criminals, use various activities to attack data. Some of their activities include phishing, data breach, identity theft and harassment. The paper has been written to assess forensic analysis of streaming multimedia. While exploring existing studies, it was realized that despite the rich availability of digital image forensics, video forensics hasn’t been explored much. This is because of the difficulty involved in analyzing the video data. Video data is always presented in a compressed form, unlike still images that are obtained in their original state. The compressed data often cancels or totally compromises the existing fingerprints, hence making it difficult to monitor or recover data. It was also revealed that, much has not been done so far as the research area is concerned. Keywords: Mobile Forensics, Cybersecurity, Streaming, Media, Video, Networks BOOK Chapter ǀ Research Nexus in IT, Law, Cyber Security & Forensics. Open Access. Distributed Free Citation: Emmanuel Tettey Okan (2022): Forensic Analysis On Streaming Multimedia Book Chapter Series on Research Nexus in IT, Law, Cyber Security & Forensics. Pp 221-226 www.isteams.net/ITlawbookchapter2022. dx.doi.org/10.22624/AIMS/CRP-BK3-P36

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Lizarti, Nora, Bambang Sugiantoro et Yudi Prayudi. « PENERAPAN COMPOSITE LOGIC DALAM MENGKOLABORASIKAN FRAMEWORK TERKAIT MULTIMEDIA FORENSIK ». JISKA (Jurnal Informatika Sunan Kalijaga) 2, n^o 1 (29 août 2017) : 26. http://dx.doi.org/10.14421/jiska.2017.21-04.

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Like the digital forensics in general, multimedia forensics requires an integrated and flexible framework that can guide the process of proof is procedurally in order to maintain the validity of a digital evidence so that it can be justified in court. But this time, the digital forensics investigation framework that develops more emphasis on computer forensic investigations in general and did not give a specific stage of multimedia forensics. Often in investigating multimedia forensics investigator uses a framework that vary depending on the type of multimedia content to be analyzed, of course it becomes inflexible and inefficient, whereas multimedia content share characteristics that allow it to be integrated into a single unit. This study develops a forensic multimedia framework by implementing the Composite Logic to collaborate on several multimedia framework and related documents. Logic Composite method is a method of modeling the distribution of structured logical modularization techniques with explicit interface in which a model consists of a set of components that are interconnected with the principle of decomposition. In other words, the application of this method will allow researchers to extract and merge several frameworks into a single unit does not eliminate the function and the basic structure of the frameworks.

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Wisdom, Frey John. « Digital Forensics In Multimedia ». Advances in Multidisciplinary and scientific Research Journal Publication 1, n^o 1 (26 juillet 2022) : 239–50. http://dx.doi.org/10.22624/aims/crp-bk3-p39.

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Digital forensics and multimedia forensics are rapidly growing disciplines where electronic information is extracted and interpreted using scientifically accepted and validated processes, to be used in and outside of a court of law. As personal computing and the internet becomes more widespread, these two fields are becoming increasingly important in law enforcement and cybercrime investigation.Digital forensics involves investigating computer systems and digital artefacts in general, while multimedia forensics is a sub-topic of digital forensics which focuses on extracting and analyzing contents such as images, videos, and audio to produce forensic evidence from both regular computer systems and special multimedia devices, such as digital cameras, voice recorders etc. This paper seeks to shed some light on digital forensics in multimedia, methods of authentication and challenges. Keywords: Forensics, Multimedia, Scrutiny, Analysis, Video, Voice, Data, Camera, Authentication BOOK Chapter ǀ Research Nexus in IT, Law, Cyber Security & Forensics. Open Access. Distributed Free Citation: Frey John Wisdom (2022): Digital Forensics In Multimedia Book Chapter Series on Research Nexus in IT, Law, Cyber Security & Forensics. Pp 239-250 www.isteams.net/ITlawbookchapter2022. dx.doi.org/10.22624/AIMS/CRP-BK3-P39

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Khan, Muhammad Khurram, Mohammed Zakariah, Hafiz Malik et Kim-Kwang Raymond Choo. « A novel audio forensic data-set for digital multimedia forensics ». Australian Journal of Forensic Sciences 50, n^o 5 (24 mars 2017) : 525–42. http://dx.doi.org/10.1080/00450618.2017.1296186.

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Nour Mohammad, Hasan Fayyad-Kazan, Mohamad Saab. « Anti- Forensics : The Tampering of Media ». International Journal on Recent and Innovation Trends in Computing and Communication 8, n^o 10 (31 octobre 2020) : 06–30. http://dx.doi.org/10.17762/ijritcc.v8i10.5447.

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In the context of forensic investigations, the traditional understanding of evidence is changing where nowadays most prosecutors, lawyers and judges heavily rely on multimedia signs. This modern shift has allowed the law enforcement to better reconstruct the crime scenes or reveal the truth of any critical event.In this paper we shed the light on the role of video, audio and photos as forensic evidences presenting the possibility of their tampering by various easy-to-use, available anti-forensics softwares. We proved that along with the forensic analysis, digital processing, enhancement and authentication via forgery detection algorithms to testify the integrity of the content and the respective source of each, differentiating between an original and altered evidence is now feasible. These operations assist the court to attain higher degree of intelligibility of the multimedia data handled and assert the information retrieved from each that support the success of the investigation process.

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Zou, Hao, Pengpeng Yang, Rongrong Ni et Yao Zhao. « Anti-Forensics of Image Contrast Enhancement Based on Generative Adversarial Network ». Security and Communication Networks 2021 (24 mars 2021) : 1–8. http://dx.doi.org/10.1155/2021/6663486.

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In the multimedia forensics community, anti-forensics of contrast enhancement (CE) in digital images is an important topic to understand the vulnerability of the corresponding CE forensic method. Some traditional CE anti-forensic methods have demonstrated their effective forging ability to erase forensic fingerprints of the contrast-enhanced image in histogram and even gray level cooccurrence matrix (GLCM), while they ignore the problem that their ways of pixel value changes can expose them in the pixel domain. In this paper, we focus on the study of CE anti-forensics based on Generative Adversarial Network (GAN) to handle the problem mentioned above. Firstly, we exploit GAN to process the contrast-enhanced image and make it indistinguishable from the unaltered one in the pixel domain. Secondly, we introduce a specially designed histogram-based loss to enhance the attack effectiveness in the histogram domain and the GLCM domain. Thirdly, we use a pixel-wise loss to keep the visual enhancement effect of the processed image. The experimental results show that our method achieves high anti-forensic attack performance against CE detectors in the pixel domain, the histogram domain, and the GLCM domain, respectively, and maintains the highest image quality compared with traditional CE anti-forensic methods.

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Ruslan, Takdir, Imam Riadi et Sunardi Sunardi. « FORENSIK MULTIMEDIA BERBASIS MOBILE MENGGUNAKAN METODE NATIONAL INSTITUTE OF JUSTICE ». Jurnal SAINTEKOM 12, n^o 1 (2 mars 2022) : 69–80. http://dx.doi.org/10.33020/saintekom.v12i1.210.

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Current technological developments make it easier for people to share information and carry out communication activities through instant messaging applications using multimedia features in the form of audio and video. Technology has been able to contribute and facilitate humans in a positive sense, but it can also be misused to carry out negative activities. In solving crime problems using instant messages, investigators need to carry out digital forensics, including on mobile devices such as smartphones. This study aims to obtain digital evidence of online drug sales scenarios via Facebook messenger and WhatsApp using four forensic tools, namely Belkasoft, Oxygen, MOBILedit, and Magnet Axiom. The National Institute of Justice (NIJ) is used as a framework with stages, namely identification, solution, testing, evaluation, and reporting of results. out of the four tools, MOBILedit cannot recover deleted audio and video while the other three tools can recover deleted audio and video.

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Marcon, Federico, Cecilia Pasquini et Giulia Boato. « Detection of Manipulated Face Videos over Social Networks : A Large-Scale Study ». Journal of Imaging 7, n^o 10 (28 septembre 2021) : 193. http://dx.doi.org/10.3390/jimaging7100193.

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The detection of manipulated videos represents a highly relevant problem in multimedia forensics, which has been widely investigated in the last years. However, a common trait of published studies is the fact that the forensic analysis is typically applied on data prior to their potential dissemination over the web. This work addresses the challenging scenario where manipulated videos are first shared through social media platforms and then are subject to the forensic analysis. In this context, a large scale performance evaluation has been carried out involving general purpose deep networks and state-of-the-art manipulated data, and studying different effects. Results confirm that a performance drop is observed in every case when unseen shared data are tested by networks trained on non-shared data; however, fine-tuning operations can mitigate this problem. Also, we show that the output of differently trained networks can carry useful forensic information for the identification of the specific technique used for visual manipulation, both for shared and non-shared data.

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Zawali, Bako, Richard A. Ikuesan, Victor R. Kebande, Steven Furnell et Arafat A-Dhaqm. « Realising a Push Button Modality for Video-Based Forensics ». Infrastructures 6, n^o 4 (2 avril 2021) : 54. http://dx.doi.org/10.3390/infrastructures6040054.

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Complexity and sophistication among multimedia-based tools have made it easy for perpetrators to conduct digital crimes such as counterfeiting, modification, and alteration without being detected. It may not be easy to verify the integrity of video content that, for example, has been manipulated digitally. To address this perennial investigative challenge, this paper proposes the integration of a forensically sound push button forensic modality (PBFM) model for the investigation of the MP4 video file format as a step towards automated video forensic investigation. An open-source multimedia forensic tool was developed based on the proposed PBFM model. A comprehensive evaluation of the efficiency of the tool against file alteration showed that the tool was capable of identifying falsified files, which satisfied the underlying assertion of the PBFM model. Furthermore, the outcome can be used as a complementary process for enhancing the evidence admissibility of MP4 video for forensic investigation.

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Zhao, H. V., Min Wu, Z. J. Wang et K. J. Ray Liu. « Forensic analysis of nonlinear collusion attacks for multimedia fingerprinting ». IEEE Transactions on Image Processing 14, n^o 5 (mai 2005) : 646–61. http://dx.doi.org/10.1109/tip.2005.846035.

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Mashhadani, Shahlaa, Hiba Al-kawaz, Nathan Clarke, Steven Furnell et Fudong Li. « The Design of a Multimedia-Forensic Analysis Tool (M-FAT) ». International Journal of Multimedia and Image Processing 8, n^o 1 (30 mars 2018) : 398–408. http://dx.doi.org/10.20533/ijmip.2042.4647.2018.0049.

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Alrobieh, Ziad Saif, et 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 février 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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Zharkikh, S. S., A. A. Godlevskii et S. A. Krivoshchekov. « The Potential of Integrated Video and Vehicle Forensic Investigation ». Theory and Practice of Forensic Science 14, n^o 2 (13 juillet 2019) : 67–83. http://dx.doi.org/10.30764/1819-2785-2019-14-2-67-83.

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In some cases, the material provided for a forensic vehicle examination may be insufficient to answer the questions placed before the experts. However, sometimes there are some multimedia files presented which by means of forensic video examination can help to discover the information missing for implementation of the vehicle expertise. This article reviews the potential of forensic video and vehicle investigations when conducting an integrated research including the investigation of circumstances of a road traffic accident. The examples from the state experts’ practice of the forensic institutions of the Russian Ministry of Justice are provided. This review is intended to introduce the video experts and the vehicle experts to the opportunities there are in the integrated research of the mechanism of road accidents.

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Kingra, Staffy, Naveen Aggarwal et Raahat Devender Singh. « Video Inter-frame Forgery Detection Approach for Surveillance and Mobile Recorded Videos ». International Journal of Electrical and Computer Engineering (IJECE) 7, n^o 2 (1 avril 2017) : 831. http://dx.doi.org/10.11591/ijece.v7i2.pp831-841.

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We are living in an age where use of multimedia technologies like digital recorders and mobile phones is increasing rapidly. On the other hand, digital content manipulating softwares are also increasing making it easy for an individual to doctor the recorded content with trivial consumption of time and wealth. Digital multimedia forensics is gaining utmost importance to restrict unethical use of such easily available tampering techniques. These days, it is common for people to record videos using their smart phones. We have also witnessed a sudden growth in the use of surveillance cameras, which we see inhabiting almost every public location. Videos recorded using these devices usually contains crucial evidence of some event occurence and thereby most susceptible to inter-frame forgery which can be easily performed by insertion/removal/replication of frame(s). The proposed forensic technique enabled detection of inter-frame forgery in H.264 and MPEG-2 encoded videos especially mobile recorded and surveillance videos. This novel method introduced objectivity for automatic detection and localization of tampering by utilizing prediction residual gradient and optical flow gradient. Experimental results showed that this technique can detect tampering with 90% true positive rate, regardless of the video codec and recording device utilized and number of frames tampered.

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Cunha, Daniel de O., Edmar A. Silva, Jorge de A. Lambert et Rafael O. Ribeiro. « Peritus Framework : Towards multimedia evidence analysis uniformization in brazilian distributed forensic model ». Forensic Science International : Digital Investigation 35 (décembre 2020) : 301089. http://dx.doi.org/10.1016/j.fsidi.2020.301089.

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Hussain, Israr, Dostdar Hussain, Rashi Kohli, Muhammad Ismail, Saddam Hussain, Syed Sajid Ullah, Roobaea Alroobaea, Wajid Ali et Fazlullah Umar. « Evaluation of Deep Learning and Conventional Approaches for Image Recaptured Detection in Multimedia Forensics ». Mobile Information Systems 2022 (15 juin 2022) : 1–10. http://dx.doi.org/10.1155/2022/2847580.

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Image recaptured from a high-resolution LED screen or a good quality printer is difficult to distinguish from its original counterpart. The forensic community paid less attention to this type of forgery than to other image alterations such as splicing, copy-move, removal, or image retouching. It is significant to develop secure and automatic techniques to distinguish real and recaptured images without prior knowledge. Image manipulation traces can be hidden using recaptured images. For this reason, being able to detect recapture images becomes a hot research topic for a forensic analyst. The attacker can recapture the manipulated images to fool image forensic system. As far as we know, there is no prior research that has examined the pros and cons of up-to-date image recaptured techniques. The main objective of this survey was to succinctly review the recent outcomes in the field of image recaptured detection and investigated the limitations in existing approaches and datasets. The outcome of this study provides several promising directions for further significant research on image recaptured detection. Finally, some of the challenges in the existing datasets and numerous promising directions on recaptured image detection are proposed to demonstrate how these difficulties might be carried into promising directions for future research. We also discussed the existing image recaptured datasets, their limitations, and dataset collection challenges.

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Ferreira, Sara, Mário Antunes et Manuel E. Correia. « A Dataset of Photos and Videos for Digital Forensics Analysis Using Machine Learning Processing ». Data 6, n^o 8 (5 août 2021) : 87. http://dx.doi.org/10.3390/data6080087.

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Deepfake and manipulated digital photos and videos are being increasingly used in a myriad of cybercrimes. Ransomware, the dissemination of fake news, and digital kidnapping-related crimes are the most recurrent, in which tampered multimedia content has been the primordial disseminating vehicle. Digital forensic analysis tools are being widely used by criminal investigations to automate the identification of digital evidence in seized electronic equipment. The number of files to be processed and the complexity of the crimes under analysis have highlighted the need to employ efficient digital forensics techniques grounded on state-of-the-art technologies. Machine Learning (ML) researchers have been challenged to apply techniques and methods to improve the automatic detection of manipulated multimedia content. However, the implementation of such methods have not yet been massively incorporated into digital forensic tools, mostly due to the lack of realistic and well-structured datasets of photos and videos. The diversity and richness of the datasets are crucial to benchmark the ML models and to evaluate their appropriateness to be applied in real-world digital forensics applications. An example is the development of third-party modules for the widely used Autopsy digital forensic application. This paper presents a dataset obtained by extracting a set of simple features from genuine and manipulated photos and videos, which are part of state-of-the-art existing datasets. The resulting dataset is balanced, and each entry comprises a label and a vector of numeric values corresponding to the features extracted through a Discrete Fourier Transform (DFT). The dataset is available in a GitHub repository, and the total amount of photos and video frames is 40,588 and 12,400, respectively. The dataset was validated and benchmarked with deep learning Convolutional Neural Networks (CNN) and Support Vector Machines (SVM) methods; however, a plethora of other existing ones can be applied. Generically, the results show a better F1-score for CNN when comparing with SVM, both for photos and videos processing. CNN achieved an F1-score of 0.9968 and 0.8415 for photos and videos, respectively. Regarding SVM, the results obtained with 5-fold cross-validation are 0.9953 and 0.7955, respectively, for photos and videos processing. A set of methods written in Python is available for the researchers, namely to preprocess and extract the features from the original photos and videos files and to build the training and testing sets. Additional methods are also available to convert the original PKL files into CSV and TXT, which gives more flexibility for the ML researchers to use the dataset on existing ML frameworks and tools.

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Kaplan, Lawrence J. « Forensic Science : An Interactive Multimedia Laboratory Program to Enhance Introductory Chemistry (Science) Courses ». Journal of Chemical Education 73, n^o 6 (juin 1996) : 527. http://dx.doi.org/10.1021/ed073p527.2.

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Flego, Clio. « Forensic Architecture : A New Photographic Language in a Factual Era ». Membrana Journal of Photography, Vol. 3, no. 1 (2018) : 70–75. http://dx.doi.org/10.47659/m4.070.art.

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A group of visual activists, architects, software developers and archaeologists as well as a multicultural team composed of artists, investigative journalists and lawyers – an organic organization. Forensic Architecture ‘Investigative aesthetic’ is based on visual aggregation on data allowing viewers to enhance their perception-cognition of events by the integrated use of augmented photography. Their works have been presented in front of a court, but also exhibited at international shows all around the world. FA expanded use of photography, integrating in the urbanistic reconstruction of frames of any kind of multimedia information collected, consider it not simply as a medium, but as a proper tool for triggering critical reflections and political action. Forensic Architecture have mainly been investigating the area of conflicts with the aim to present counter- investigation on unclear circumstances, often underlining social constructs in the public forum. The particular role that FA plays, claiming social truth and assigning to photography the function to be a “civil act,” remarks its place in the history of war photography, and underlines the importance of also having a contra-culture in a post- industrial society, permeated by the presence of technology. Keywords: evidence, Forensic Architecture, forensic reconstruction of event, photography, truth-value

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Premanand Ghadekar, Vaibhavi Shetty, Prapti Maheshwari, Raj Shah, Anish Shaha et Vaishnav Sonawane. « Non-Facial Video Spatiotemporal Forensic Analysis Using Deep Learning Techniques ». Proceedings of Engineering and Technology Innovation 23 (1 janvier 2023) : 01–14. http://dx.doi.org/10.46604/peti.2023.10290.

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Digital content manipulation software is working as a boon for people to edit recorded video or audio content. To prevent the unethical use of such readily available altering tools, digital multimedia forensics is becoming increasingly important. Hence, this study aims to identify whether the video and audio of the given digital content are fake or real. For temporal video forgery detection, the convolutional 3D layers are used to build a model which can identify temporal forgeries with an average accuracy of 85% on the validation dataset. Also, the identification of audio forgery, using a ResNet-34 pre-trained model and the transfer learning approach, has been achieved. The proposed model achieves an accuracy of 99% with 0.3% validation loss on the validation part of the logical access dataset, which is better than earlier models in the range of 90-95% accuracy on the validation set.

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Hewson, Lindsay, et Jane Goodman-Delahunty. « Using multimedia to support jury understanding of DNA profiling evidence ». Australian Journal of Forensic Sciences 40, n^o 1 (juin 2008) : 55–64. http://dx.doi.org/10.1080/00450610802050782.

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Shepitko, V. « FORMATION OF CRIMINALISTICS AND FORENSIC DIDACTICS IN UKRAINE ». Theory and Practice of Forensic Science and Criminalistics 22, n^o 2 (12 novembre 2020) : 7–19. http://dx.doi.org/10.32353/khrife.2.2020.01.

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The article is devoted to formation, development and current status of criminalistics as a science and academic discipline in Ukraine. Attention is drawn to some trends in criminalistics in modern conditions. The variability of forensic knowledge is associated with the scientific and technological progress of modern society. Special attention is drawn to the role of criminalistics in scientific support of not only proof procedure, but also of various law enforcement procedures. The use of forensic knowledge is relevant in the practical activities of various lawyers: prosecutor, investigator, detective, judge, lawyer, notary, legal adviser, etc. The relationship between activities optimization of the court and law enforcement agencies with introduction of criminalistics innovations is established. The approaches to teaching criminalistics for law students in Ukrainian universities are considered. The necessity of teaching criminalistics to law students of various specializations is substantiated. The volume of workload, period of study, forms of education, information transfer methods, methods of mastering practical skills are defined as parameters for teaching criminalistics and criminalistics disciplines. The role of modernized methods in teaching criminalistics is justified. The following modernized methods are defined: business games, solving non-standard cognitive tasks, quick tests, the use of multimedia tools and electronic data base, technical tools, etc. The possibilities of using the criminalistics training ground and criminalistics museum in the course of practical seminars and laboratory works are demonstrated.

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Khan, Abdullah Ayub, Mueen Uddin, Aftab Ahmed Shaikh, Asif Ali Laghari et Adil E. Rajput. « MF-Ledger : Blockchain Hyperledger Sawtooth-Enabled Novel and Secure Multimedia Chain of Custody Forensic Investigation Architecture ». IEEE Access 9 (2021) : 103637–50. http://dx.doi.org/10.1109/access.2021.3099037.

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Negka, Lydia, et Georgios Spathoulas. « Towards Secure, Decentralised, and Privacy Friendly Forensic Analysis of Vehicular Data ». Sensors 21, n^o 21 (21 octobre 2021) : 6981. http://dx.doi.org/10.3390/s21216981.

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The automotive industry has been transformed through technological progress during the past decade. Vehicles are equipped with multiple computing devices that offer safety, driving assistance, or multimedia services. Despite these advancements, when an incident occurs, such as a car crash, the involved parties often do not take advantage of the technological capabilities of modern vehicles and attempt to assign liability for the incident to a specific vehicle based upon witness statements. In this paper, we propose a secure, decentralized, blockchain-based platform that can be employed to store encrypted position and velocity values for vehicles in a smart city environment. Such data can be decrypted when the need arises, either through the vehicle driver’s consent or through the consensus of different authorities. The proposed platform also offers an automated way to resolve disputes between involved parties. A simulation has been conducted upon a mobility traffic dataset for a typical day in the city of Cologne to assess the applicability of the proposed methodology to real-world scenarios and the infrastructure requirements that such an application would have.

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Agrawal, Vinayak, et Shashikala Tapaswi. « Forensic analysis of Google Allo messenger on Android platform ». Information & ; Computer Security 27, n^o 1 (11 mars 2019) : 62–80. http://dx.doi.org/10.1108/ics-03-2017-0011.

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Purpose The purpose of this paper is to conduct a forensic analysis of Google Allo messenger on an Android-based mobile phone. The focus was on the analysis of the data stored by this application in the internal memory of the mobile device, with minimal use of third-party applications. The findings were compared with the already existing works on this topic. Android is the most popular operating system for mobile devices, and these devices often contain a massive amount of personal information about the user such as photos and contact details. Analysis of these applications is required in case of a forensic investigation and makes the process easier for forensic analysts. Design/methodology/approach Logical acquisition of the data stored by these applications was performed. A locked Android device was used for this purpose. Some scripts are presented to help in data acquisition using Android Debug Bridge (ADB). Manual forensic analysis of the device image was performed to see whether the activities carried out on these applications are stored in the internal memory of the device. A comparative analysis of an existing mobile forensic tool was also performed to show the effectiveness of the methodology adopted. Findings Forensic artifacts were recovered from Allo application. Multimedia content such as images were also retrieved from the internal memory. Research limitations/implications As this study was conducted for forensic analysis, it assumed that the mobile device used already has USB debugging enabled on it, although this might not be the applicable in some of the cases. This work provides an optimal approach to acquiring artifacts with minimal use of third-party applications. Practical implications Most of the mobile devices contain messaging application such as Allo installed. A large amount of personal information can be obtained from the forensic analysis of these applications, which can be useful in any criminal investigation. Originality/value This is the first study which focuses on the Google Allo application. The proposed methodology was able to extract almost as much as the data obtained using earlier approaches, but with minimal third-party application usage.

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da Silveira, Claudinei Morin, Rafael T. de Sousa Jr, Robson de Oliveira Albuquerque, Georges D. Amvame Nze, Gildásio Antonio de Oliveira Júnior, Ana Lucila Sandoval Orozco et Luis Javier García Villalba. « Methodology for Forensics Data Reconstruction on Mobile Devices with Android Operating System Applying In-System Programming and Combination Firmware ». Applied Sciences 10, n^o 12 (20 juin 2020) : 4231. http://dx.doi.org/10.3390/app10124231.

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This paper proposes a new forensic analysis methodology that combines processes, techniques, and tools for physical and logical data acquisition from mobile devices. The proposed methodology allows an overview of the use of the In-System Programming (ISP) technique with the usage of Combination Firmware, aligned with specific collection and analysis processes. The carried out experiments show that the proposed methodology is convenient and practical and provides new possibilities for data acquisition on devices that run the Android Operating System with advanced protection mechanisms. The methodology is also feasible in devices compatible with the usage of Joint Test Action Group (JTAG) techniques and which use Embedded Multimedia Card (eMMC) or Embedded Multi-Chip Package (eMCP) as main memory. The techniques included in the methodology are effective on encrypted devices, in which the JTAG and Chip-Off techniques prove to be ineffective, especially on those that have an unauthorized access protection mechanism enabled, such as lock screen password, blocked bootloader, and Factory Reset Protection (FRP) active. Studies also demonstrate that data preservation and integrity are maintained, which is critical to a digital forensic process.

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Haschke, G., et M. Diener. « Concept and Realization of a Multimedia Program for Veterinary Physiology ». Journal of Veterinary Medicine Series A 50, n^o 6 (août 2003) : 274–79. http://dx.doi.org/10.1046/j.1439-0442.2003.00535.x.

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Renza, Diego, Jaisson Vargas et Dora M. Ballesteros. « Robust Speech Hashing for Digital Audio Forensics ». Applied Sciences 10, n^o 1 (28 décembre 2019) : 249. http://dx.doi.org/10.3390/app10010249.

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The verification of the integrity and authenticity of multimedia content is an essential task in the forensic field, in order to make digital evidence admissible. The main objective is to establish whether the multimedia content has been manipulated with significant changes to its content, such as the removal of noise (e.g., a gunshot) that could clarify the facts of a crime. In this project we propose a method to generate a summary value for audio recordings, known as hash. Our method is robust, which means that if the audio has been modified slightly (without changing its significant content) with perceptual manipulations such as MPEG-4 AAC, the hash value of the new audio is very similar to that of the original audio; on the contrary, if the audio is altered and its content changes, for example with a low pass filter, the new hash value moves away from the original value. The method starts with the application of MFCC (Mel-frequency cepstrum coefficients) and the reduction of dimensions through the analysis of main components (principal component analysis, PCA). The reduced data is encrypted using as inputs two values from a particular binarization system using Collatz conjecture as the basis. Finally, a robust 96-bit code is obtained, which varies little when perceptual modifications are made to the signal such as compression or amplitude modification. According to experimental tests, the BER (bit error rate) between the hash value of the original audio recording and the manipulated audio recording is low for perceptual manipulations, i.e., 0% for FLAC and re-quantization, 1% in average for volume (−6 dB gain), less than 5% in average for MPEG-4 and resampling (using the FIR anti-aliasing filter); but more than 25% for non-perceptual manipulations such as low pass filtering (3 kHz, fifth order), additive noise, cutting and copy-move.

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Asokan, R., et T. Vijayakumar. « Design of WhatsApp Image Folder Categorization Using CNN Method in the Android Domain ». September 2021 3, n^o 3 (16 octobre 2021) : 180–95. http://dx.doi.org/10.36548/jucct.2021.3.003.

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Recently, the use of different social media platforms such as Twitter, Facebook, and WhatsApp have increased significantly. A vast number of static images and motion frame pictures posted on such platforms get stored in the device folder making it critical to identify the social network of the downloaded images in the android domain. This is a multimedia forensic job with major cyber security consequences and is said to be accomplished using unique traces contained in picture material (SNs). Therefore, this proposal has been endeavoured to construct a new framework called FusionNet to combine two well-established single shared Convolutional Neural Networks (CNN) to accelerate the search. Moreover, the FusionNet has been found to improve classification accuracy. Image searching is one of the challenging issues in the android domain besides being a time-consuming process. The goal of the proposed network's architecture and training is to enhance the forensic information included in the digital pictures shared on social media. Furthermore, several network designs for the categorization of WhatsApp pictures have been compared and this suggested method has shown better performance in the comparison. The proposed framework's overall performance was measured using the performance metrics.

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Lago, Federica, Quoc-Tin Phan et Giulia Boato. « Visual and Textual Analysis for Image Trustworthiness Assessment within Online News ». Security and Communication Networks 2019 (14 avril 2019) : 1–14. http://dx.doi.org/10.1155/2019/9236910.

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The majority of news published online presents one or more images or videos, which make the news more easily consumed and therefore more attractive to huge audiences. As a consequence, news with catchy multimedia content can be spread and get viral extremely quickly. Unfortunately, the availability and sophistication of photo editing software are erasing the line between pristine and manipulated content. Given that images have the power of bias and influence the opinion and behavior of readers, the need of automatic techniques to assess the authenticity of images is straightforward. This paper aims at detecting images published within online news that have either been maliciously modified or that do not represent accurately the event the news is mentioning. The proposed approach composes image forensic algorithms for detecting image tampering, and textual analysis as a verifier of images that are misaligned to textual content. Furthermore, textual analysis can be considered as a complementary source of information supporting image forensics techniques when they falsely detect or falsely ignore image tampering due to heavy image postprocessing. The devised method is tested on three datasets. The performance on the first two shows interesting results, with F1-score generally higher than 75%. The third dataset has an exploratory intent; in fact, although showing that the methodology is not ready for completely unsupervised scenarios, it is possible to investigate possible problems and controversial cases that might arise in real-world scenarios.

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Cahyani, Niken Dwi Wahyu, Ben Martini et Kim-Kwang Raymond Choo. « Effectiveness of multimedia presentations in improving understanding of technical terminologies and concepts : a pilot study ». Australian Journal of Forensic Sciences 49, n^o 1 (29 janvier 2016) : 106–22. http://dx.doi.org/10.1080/00450618.2015.1128968.

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He, Peisong, Hongxia Wang, Ruimei Zhang et Yue Li. « A Two-Stage Cascaded Detection Scheme for Double HEVC Compression Based on Temporal Inconsistency ». Security and Communication Networks 2021 (19 avril 2021) : 1–14. http://dx.doi.org/10.1155/2021/5568351.

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Nowadays, verifying the integrity of digital videos is significant especially for applications about multimedia communication. In video forensics, detection of double compression can be treated as the first step to analyze whether a suspicious video undergoes any tampering operations. In the last decade, numerous detection methods have been proposed to address this issue, but most existing methods design a universal detector which is hard to handle various recompression settings efficiently. In this work, we found that the statistics of different Coding Unit (CU) types have dissimilar properties when original videos are recompressed by the increased and decreased bit rates. It motivates us to propose a two-stage cascaded detection scheme for double HEVC compression based on temporal inconsistency to overcome limitations of existing methods. For a given video, CU information maps are extracted from each short-time video clip using our proposed value mapping strategy. In the first detection stage, a compact feature is extracted based on the distribution of different CU types and Kullback–Leibler divergence between temporally adjacent frames. This detection feature is fed into the Support Vector Machine classifier to identify abnormal frames with the increased bit rate. In the second stage, a shallow convolutional neural network equipped with dense connections is designed carefully to learn robust spatiotemporal representations, which can identify abnormal frames with the decreased bit rate whose forensic traces are less detectable. In experiments, the proposed method can achieve more promising detection accuracy compared with several state-of-the-art methods under various coding parameter settings, especially when the original video is recompressed with a low quality (e.g., more than 8%).

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Dureja, Aman, et Payal Pahwa. « Image retrieval techniques : a survey ». International Journal of Engineering & ; Technology 7, n^o 1.2 (28 décembre 2017) : 215. http://dx.doi.org/10.14419/ijet.v7i1.2.9231.

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In the recent years, the development in computer technologies and multimedia applications has led to the production of huge digital images and large image databases, and it is increasing rapidly. There are several different areas in which image retrieval plays a crucial role like Medical systems, Forensic Labs, Tourism Promotion, etc. Thus retrieval of similar images is a challenge. To tackle this rapid growth in digital repositories it is necessary to develop image retrieval systems, which can operate on large databases. There are basically three techniques, which is useful for efficient retrieval of images. With these techniques, the number of methods has been modified for the efficient image retrieval of images. In this paper, we presented the survey of different techniques that has been used starting from Image retrieval using visual features and latest by the deep learning with CNN that contains the number of layers and now becomes the best base method for retrieval of images from the large databases. In the last section, we have made the analysis between various developed techniques and showed the advantages and disadvantages of various techniques.

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.., Ossama, et Mhmed Algrnaodi. « Deep Learning Fusion for Attack Detection in Internet of Things Communications ». Fusion : Practice and Applications 9, n^o 2 (2022) : 27–47. http://dx.doi.org/10.54216/fpa.090203.

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The increasing deep learning techniques used in multimedia and networkIoT solve many problems and increase performance. Securing the deep learning models, multimedia, and networkIoT has become a major area of research in the past few years which is considered to be a challenge during generative adversarial attacks over the multimedia or networkIoT. Many efforts and studies try to provide intelligent forensics techniques to solve security issues. This paper introduces a holistic organization of intelligent multimedia forensics that involve deep learning fusion, multimedia, and networkIoT forensics to attack detection. We highlight the importance of using deep learning fusion techniques to obtain intelligent forensics and security over multimedia or NetworkIoT. Finally, we discuss the key challenges and future directions in the area of intelligent multimedia forensics using deep learning fusion techniques.

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S, Manjunatha, et Malini M. Patil. « Efficient resampling features and convolution neural network model for image forgery detection ». Indonesian Journal of Electrical Engineering and Computer Science 25, n^o 1 (1 janvier 2022) : 183. http://dx.doi.org/10.11591/ijeecs.v25.i1.pp183-190.

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The extended utilization of picture-enhancing or manipulating tools has led to ease of manipulating multimedia data which includes digital images. These manipulations will disturb the truthfulness and lawfulness of images, resulting in misapprehension, and might disturb social security. The image forensic approach has been employed for detecting whether or not an image has been manipulated with the usage of positive attacks which includes splicing, and copy-move. This paper provides a competent tampering detection technique using resampling features and convolution neural network (CNN). In this model range spatial filtering (RSF)-CNN, throughout preprocessing the image is divided into consistent patches. Then, within every patch, the resampling features are extracted by utilizing affine transformation and the Laplacian operator. Then, the extracted features are accumulated for creating descriptors by using CNN. A wide-ranging analysis is performed for assessing tampering detection and tampered region segmentation accuracies of proposed RSF-CNN based tampering detection procedures considering various falsifications and post-processing attacks which include joint photographic expert group (JPEG) compression, scaling, rotations, noise additions, and more than one manipulation. From the achieved results, it can be visible the RSF-CNN primarily based tampering detection with adequately higher accurateness than existing tampering detection methodologies.

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Amerini, Irene, Aris Anagnostopoulos, Luca Maiano et Lorenzo Ricciardi Celsi. « Deep Learning for Multimedia Forensics ». Foundations and Trends® in Computer Graphics and Vision 12, n^o 4 (2021) : 309–457. http://dx.doi.org/10.1561/0600000096.

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Fu, Lucy, Michael Swete, Daniel Selgrade, Clarence W. Chan, Raven Rodriguez, Kristy Wolniak et Luis Z. Blanco. « Virtual Pathology Elective Provides Uninterrupted Medical Education and Impactful Pathology Education During the COVID-19 Pandemic ». Academic Pathology 8 (1 janvier 2021) : 237428952110102. http://dx.doi.org/10.1177/23742895211010275.

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As students do not qualify as essential health care workers, medical education faced severe disruptions during the COVID-19 pandemic including initial suspension of all in-person lectures and on-site rotations. Our Pathology Department was among the first at Northwestern to offer a completely virtual rotation with the goals of: (1) providing a comprehensive introduction to the practice of anatomic and clinical pathology, (2) emphasizing uninterrupted and continued excellence in education, and (3) minimizing exposure risk during the pandemic. The innovative 2-week curriculum incorporated diverse teaching modalities including live and recorded lectures; live and recorded video demonstrations; interactive small group discussions; interactive virtual sign-outs; and written and multimedia assignments, quizzes, and projects. The virtual elective ran from March to July 2020 with 52 total participating medical students. On post-rotation evaluations, students rated the pathology virtual elective 4.7/5.0 compared to other virtual rotations and 4.0/5.0 compared to all rotations (including in-person and virtual). Furthermore, continual improvements were made to the established framework based on rotation feedback such that curriculum content was more abundant and more favorably rated by the last cohort when compared to the first. Finally, although students identified interest in over 10 different medical specialties, all participants expressed increased interest in choosing pathology as a specialty and better understanding of pathology’s role in patient care. We hope our detailed description of creating and evaluating a completely virtual elective rotation serves as a model for other departments to improve pathology education and visibility.

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Mainoo, Bernard. « Digital Multimedia Tampering Detection for Forensics Analysis ». Advances in Multidisciplinary and scientific Research Journal Publication 1, n^o 1 (22 juillet 2022) : 81–90. http://dx.doi.org/10.22624/aims/crp-bk3-p14.

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In the virtual multimedia era, digital forensics is turning into a rising location of studies way to the huge quantity of picture and video documents generated. Ensuring the integrity of such media is of top-notch significance in lots of situations. This mission has end up extra complex, particularly with the development of symmetrical and asymmetrical community systems which make their authenticity tough. Consequently, it's far definitely vital to find out all feasible modes of manipulation through the improvement of latest forensics detector tools. For example, the symmetry and asymmetry inconsistencies associated with visible characteristic residences are capacity while carried out at a couple of scales and locations. We discover right here this subject matter and advocate a comprehensible smooth taxonomy and a deep assessment of the brand-new studies regarding multimedia forgery detection. Then, an in-intensity dialogue and destiny guidelines for similarly research are provided. This painting gives a possibility for researchers to apprehend the cutting-edge lively subject and to assist them broaden and examine their very own picture/video forensics approaches. Keywords: Digital forensics, Multimedia tampering, Image/video processing, Watermarking, pattern recognition, Active/Passive Tampering Detection

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Battiato, Sebastiano, Sabu Emmanuel, Adrian Ulges et Marcel Worring. « Multimedia in Forensics, Security, and Intelligence ». IEEE Multimedia 19, n^o 1 (janvier 2012) : 17–19. http://dx.doi.org/10.1109/mmul.2012.10.

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Rocha, Anderson, Shujun Li, C. C. Jay Kuo, Alessandro Piva et Jiwu Huang. « Data-driven multimedia forensics and security ». Journal of Visual Communication and Image Representation 55 (août 2018) : 447–48. http://dx.doi.org/10.1016/j.jvcir.2018.06.023.

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Levesque, Deborah A., Mary-Margaret Driskell, Janice M. Prochaska et James O. Prochaska. « Acceptability of a Stage-Matched Expert System Intervention for Domestic Violence Offenders ». Violence and Victims 23, n^o 4 (août 2008) : 432–45. http://dx.doi.org/10.1891/0886-6708.23.4.432.

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Most interventions for men who batter are standardized and “one-size-fits-all,” neglecting individual differences in readiness to change. A multimedia expert system intervention based on the transtheoretical model (the “stage model”) was developed as an adjunct to traditional court-mandated programs. The expert system assesses stage of change, decisional balance, self-efficacy, and processes of change and provides immediate individualized stage-matched feedback designed to increase readiness to end the violence. Fifty-eight male batterer intervention program clients were invited by agency staff to complete an expert system session and an evaluation of the program; 33 men were recruited at program intake and the remainder from ongoing groups. Responses to the intervention were very positive. For example, 87% of participants reported that they found the program to be easy to use, and 98% said it could probably or definitely help them change their attitudes or behaviors. Findings provide encouraging evidence of the acceptability of this stage-matched approach to intervention for domestic violence offenders.

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Su, Kaiqing, Nili Tian et Qing Pan. « Multimedia source identification using an improved weight photo response non-uniformity noise extraction model in short compressed videos ». Forensic Science International : Digital Investigation 42-43 (octobre 2022) : 301473. http://dx.doi.org/10.1016/j.fsidi.2022.301473.

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Pasquini, Cecilia. « Statistical and deterministic approaches for multimedia forensics ». ELCVIA Electronic Letters on Computer Vision and Image Analysis 15, n^o 2 (4 novembre 2016) : 16. http://dx.doi.org/10.5565/rev/elcvia.984.

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HU, Yong-jian, Bei-bei LIU et Qian-hua HE. « Survey on techniques of digital multimedia forensics ». Journal of Computer Applications 30, n^o 3 (2 avril 2010) : 657–62. http://dx.doi.org/10.3724/sp.j.1087.2010.00657.

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Casey, Eoghan. « New developments in digital & ; multimedia forensics ». Digital Investigation 10, n^o 3 (octobre 2013) : 205–6. http://dx.doi.org/10.1016/j.diin.2013.09.001.

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Bourouis, Sami, Roobaea Alroobaea, Abdullah M. Alharbi, Murad Andejany et Saeed Rubaiee. « Recent Advances in Digital Multimedia Tampering Detection for Forensics Analysis ». Symmetry 12, n^o 11 (1 novembre 2020) : 1811. http://dx.doi.org/10.3390/sym12111811.

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In the digital multimedia era, digital forensics is becoming an emerging area of research thanks to the large amount of image and video files generated. Ensuring the integrity of such media is of great importance in many situations. This task has become more complex, especially with the progress of symmetrical and asymmetrical network structures which make their authenticity difficult. Consequently, it is absolutely imperative to discover all possible modes of manipulation through the development of new forensics detector tools. Although many solutions have been developed, tamper-detection performance is far from reliable and it leaves this problem widely open for further investigation. In particular, many types of multimedia fraud are difficult to detect because some evidences are not exploited. For example, the symmetry and asymmetry inconsistencies related to visual feature properties are potential when applied at multiple scales and locations. We explore here this topic and propose an understandable soft taxonomy and a deep overview of the latest research concerning multimedia forgery detection. Then, an in-depth discussion and future directions for further investigation are provided. This work offers an opportunity for researchers to understand the current active field and to help them develop and evaluate their own image/video forensics approaches.

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Ansari, Mohd Dilshad, et Mohd Wajid. « Editorial : Image, Video Forensics, and Multimedia Content Security ». Recent Advances in Computer Science and Communications 14, n^o 2 (20 mai 2021) : 342–43. http://dx.doi.org/10.2174/266625581402210121143043.

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Qin, Chuan, Zhenxing Qian, Xiaolong Li et Jinwei Wang. « Artificial Intelligence Oriented Information Hiding and Multimedia Forensics ». IETE Technical Review 38, n^o 1 (2 janvier 2021) : 1–4. http://dx.doi.org/10.1080/02564602.2021.1879422.

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Coester, Dana. « The Forensics of Desire : Deconstructing Narrative in Multimedia ». International Journal of the Image 1, n^o 3 (2011) : 19–38. http://dx.doi.org/10.18848/2154-8560/cgp/v01i03/44210.

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Zhao, H. Vicky, W. Sabrina Lin et K. J. Ray Liu. « Behavior modeling and forensics for multimedia social networks ». IEEE Signal Processing Magazine 26, n^o 1 (janvier 2009) : 118–39. http://dx.doi.org/10.1109/msp.2008.930648.

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