Relevant bibliographies by topics / Forensics and counter-forensics

Academic literature on the topic 'Forensics and counter-forensics'

Author: Grafiati
Published: 14 March 2023

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Journal articles on the topic "Forensics and counter-forensics"

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Keenan, Thomas. "Counter-forensics and Photography." Grey Room 55 (April 2014): 58–77. http://dx.doi.org/10.1162/grey_a_00141.

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Kang, Xiangui, Jingxian Liu, Hongmei Liu, and Z. Jane Wang. "Forensics and counter anti-forensics of video inter-frame forgery." Multimedia Tools and Applications 75, no. 21 (July 12, 2015): 13833–53. http://dx.doi.org/10.1007/s11042-015-2762-7.

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Yang, Pengpeng, Daniele Baracchi, Rongrong Ni, Yao Zhao, Fabrizio Argenti, and Alessandro Piva. "A Survey of Deep Learning-Based Source Image Forensics." Journal of Imaging 6, no. 3 (March 4, 2020): 9. http://dx.doi.org/10.3390/jimaging6030009.

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Image source forensics is widely considered as one of the most effective ways to verify in a blind way digital image authenticity and integrity. In the last few years, many researchers have applied data-driven approaches to this task, inspired by the excellent performance obtained by those techniques on computer vision problems. In this survey, we present the most important data-driven algorithms that deal with the problem of image source forensics. To make order in this vast field, we have divided the area in five sub-topics: source camera identification, recaptured image forensic, computer graphics (CG) image forensic, GAN-generated image detection, and source social network identification. Moreover, we have included the works on anti-forensics and counter anti-forensics. For each of these tasks, we have highlighted advantages and limitations of the methods currently proposed in this promising and rich research field.
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Irons, Alastair, and Jacques Ophoff. "Aspects of Digital Forensics in South Africa." Interdisciplinary Journal of Information, Knowledge, and Management 11 (2016): 273–83. http://dx.doi.org/10.28945/3576.

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This paper explores the issues facing digital forensics in South Africa. It examines particular cyber threats and cyber threat levels for South Africa and the challenges in addressing the cybercrimes in the country through digital forensics. The paper paints a picture of the cybercrime threats facing South Africa and argues for the need to develop a skill base in digital forensics in order to counter the threats through detection of cybercrime, by analyzing cybercrime reports, consideration of current legislation, and an analysis of computer forensics course provision in South African universities. The paper argues that there is a need to develop digital forensics skills in South Africa through university programs, in addition to associated training courses. The intention in this paper is to promote debate and discussion in order to identify the cyber threats to South Africa and to encourage the development of a framework to counter the threats – through legislation, high tech law enforcement structures and protocols, digital forensics education, digital forensics skills development, and a public and business awareness of cybercrime threats.
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Fuller, Matthew, and Nikita Mazurov. "A Counter-Forensic Audit Trail: Disassembling the Case of The Hateful Eight." Theory, Culture & Society 36, no. 6 (May 15, 2019): 171–96. http://dx.doi.org/10.1177/0263276419840418.

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Forensics is proposed as a means to understand, trace, and recompile data and computational activities. It has a securitocratic dimension and one that is being developed as a means of opening processes, events and systems into a more public state. This article proposes an analysis of forces at play in the circulation of a ‘screener’ of Quentin Tarantino’s The Hateful Eight and associated files, to suggest that forensic approaches used to control flows of data may be repurposed for dissemination. The article maps a brief history of digital forensics and sets out some of its political entailments, indicating further lines of enquiry regarding the inter-relation of technosocial powers constituted in the interactions between forensics and counter-measures. The article proposes that the posthumanities are partially constituted by a renewed relationship between questions of culture, subjectivity, knowledge and the technical. Some propositions for the technical as grounds for cultural politics are made.
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Iqbal, Saima, Wilayat Khan, Abdulrahman Alothaim, Aamir Qamar, Adi Alhudhaif, and Shtwai Alsubai. "Proving Reliability of Image Processing Techniques in Digital Forensics Applications." Security and Communication Networks 2022 (March 31, 2022): 1–17. http://dx.doi.org/10.1155/2022/1322264.

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Binary images have found its place in many applications, such as digital forensics involving legal documents, authentication of images, digital books, contracts, and text recognition. Modern digital forensics applications involve binary image processing as part of data hiding techniques for ownership protection, copyright control, and authentication of digital media. Whether in image forensics, health, or other fields, such transformations are often implemented in high-level languages without formal foundations. The lack of formal foundation questions the reliability of the image processing techniques and hence the forensic results loose their legal significance. Furthermore, counter-forensics can impede or mislead the forensic analysis of the digital images. To ensure that any image transformation meet high standards of safety and reliability, more rigorous methods should be applied to image processing applications. To verify the reliability of these transformations, we propose to use formal methods based on theorem proving that can fulfil high standards of safety. To formally investigate binary image processing, in this paper, a reversible formal model of the binary images is defined in the Proof Assistant Coq. Multiple image transformation methods are formalized and their reliability properties are proved. To analyse real-life RGB images, a prototype translator is developed that reads RGB images and translate them to Coq definitions. As the formal definitions and proof scripts can be validated automatically by the computer, this raises the reliability and legal significance of the image forensic applications.
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Stevanović, Miroslav, and Dragan Đurđević. "The role of computer forensics in the fight against terrorism." Megatrend revija 17, no. 1 (2020): 129–42. http://dx.doi.org/10.5937/megrev2001129s.

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In this paper, the authors examine the adequacy of the counter-terrorism concept, which does not envisage institutional responsibility for collecting, processing, and fixing traces of cyber-related terrorist activities. The starting point is the fact that today numerous human activities and communication take place in the cyberspace. Firstly, the focus is on the aspects of terrorism that present a generator of challenges to social stability and, in this context, the elements of the approach adopted by the current National Security Strategy of the Republic of Serbia. In this analysis, adequacy is evaluated from the point of view of functionality. In this sense, it is an attempt to present elements that influence the effectiveness of counter-terrorism in the information age. Related to this is the specification of the role that digital forensics can play in this area. The conclusion is that an effective counter-terrorism strategy must necessarily encompass the institutional incorporation of digital forensics since it alone can contribute to the timely detection or assertion of responsibility for terrorism in a networked computing environment.
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Baracchi, Daniele, Dasara Shullani, Massimo Iuliani, Damiano Giani, and Alessandro Piva. "Camera Obscura: Exploiting in-camera processing for image counter forensics." Forensic Science International: Digital Investigation 38 (September 2021): 301213. http://dx.doi.org/10.1016/j.fsidi.2021.301213.

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De Rosa, Alessia, Marco Fontani, Matteo Massai, Alessandro Piva, and Mauro Barni. "Second-Order Statistics Analysis to Cope With Contrast Enhancement Counter-Forensics." IEEE Signal Processing Letters 22, no. 8 (August 2015): 1132–36. http://dx.doi.org/10.1109/lsp.2015.2389241.

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Doyoddorj, Munkhbaatar, and Kyung-Hyune Rhee. "A Targeted Counter-Forensics Method for SIFT-Based Copy-Move Forgery Detection." KIPS Transactions on Computer and Communication Systems 3, no. 5 (May 31, 2014): 163–72. http://dx.doi.org/10.3745/ktccs.2014.3.5.163.

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Dissertations / Theses on the topic "Forensics and counter-forensics"

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Nowroozi, Ehsan. "Machine Learning Techniques for Image Forensics in Adversarial Setting." Doctoral thesis, Università di Siena, 2020. http://hdl.handle.net/11365/1096177.

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The use of machine-learning for multimedia forensics is gaining more and more consensus, especially due to the amazing possibilities offered by modern machine learning techniques. By exploiting deep learning tools, new approaches have been proposed whose performance remarkably exceed those achieved by state-of-the-art methods based on standard machine-learning and model-based techniques. However, the inherent vulnerability and fragility of machine learning architectures pose new serious security threats, hindering the use of these tools in security-oriented applications, and, among them, multimedia forensics. The analysis of the security of machine learning-based techniques in the presence of an adversary attempting to impede the forensic analysis, and the development of new solutions capable to improve the security of such techniques is then of primary importance, and, recently, has marked the birth of a new discipline, named Adversarial Machine Learning. By focusing on Image Forensics and image manipulation detection in particular, this thesis contributes to the above mission by developing novel techniques for enhancing the security of binary manipulation detectors based on machine learning in several adversarial scenarios. The validity of the proposed solutions has been assessed by considering several manipulation tasks, ranging from the detection of double compression and contrast adjustment, to the detection of geometric transformations and ltering operations.
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Books on the topic "Forensics and counter-forensics"

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Buchanan, Ben. The Defender’s View. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780190665012.003.0004.

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This chapter examines defensive cyber operations in a fashion similar to kill chain analysis. It presents an outline of how baseline network defense is done, and what technologies and techniques contribute to that mission. This includes memory forensics, penetration testing, and incident response. It shows as well how those efforts are likely to be insufficient, and how advanced states have an incentive to go further and intrude into other states’ networks for defensive reasons—operations that are sometimes called counter-computer network exploitation. It is these intrusions, which are genuinely defensive, that can be misperceived and interpreted as offensive intrusions—leading to a cycle of escalation.
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Book chapters on the topic "Forensics and counter-forensics"

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Rodger, Johnny. "Counter-forensics." In Key Essays, 78–82. London: Routledge, 2021. http://dx.doi.org/10.4324/9781003186922-11.

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Böhme, Rainer, and Matthias Kirchner. "Counter-Forensics: Attacking Image Forensics." In Digital Image Forensics, 327–66. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-0757-7_12.

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Neha Singh and Sandeep Joshi. "Digital Image Forensics and Counter Anti-forensics." In Proceedings of the International Conference on Recent Cognizance in Wireless Communication & Image Processing, 805–11. New Delhi: Springer India, 2016. http://dx.doi.org/10.1007/978-81-322-2638-3_90.

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Keenan, Thomas. "Counter-forensics and photography 1." In The Routledge Companion to Photography Theory, 276–92. New York : Routledge, 2020.: Routledge, 2019. http://dx.doi.org/10.4324/9781315727998-19.

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Lai, ShiYue, and Rainer Böhme. "Countering Counter-Forensics: The Case of JPEG Compression." In Information Hiding, 285–98. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-24178-9_20.

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Rodrigues, Marcos A., and Alan Robinson. "Fast 3D Recognition for Forensics and Counter-Terrorism Applications." In Advanced Information and Knowledge Processing, 95–109. London: Springer London, 2011. http://dx.doi.org/10.1007/978-1-4471-2140-4_7.

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Li, Wenjie, Benedetta Tondi, Rongrong Ni, and Mauro Barni. "Increased-Confidence Adversarial Examples for Deep Learning Counter-Forensics." In Pattern Recognition. ICPR International Workshops and Challenges, 411–24. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-68780-9_34.

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Pic, Marc Michel, Gaël Mahfoudi, Anis Trabelsi, and Jean-Luc Dugelay. "Face Manipulation Detection in Remote Operational Systems." In Handbook of Digital Face Manipulation and Detection, 413–36. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-87664-7_19.

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AbstractIn this chapter, we present the various categories of Face Manipulation and their use within different remote operational systems. We then use the example of remote identity document onboarding systems to illustrate how each category can be used in practice to compromise such a system. After a definition of the different Face Manipulation categories and the common algorithms used to produce them, we go through the various manipulation detection algorithms and common image and video forgery datasets. We then introduce some known counter-forensics methods that can be used by an attacker to avoid detection. Knowing the detection methods and the counter-forensic, we present how we can build up a safer system by using the correct methods at the correct time. But also how knowledge about the tampering process could be used to design the user experience to make the systems harder to compromise. We complete this review by the standardisation effort and legal aspect on the matter. And we conclude by discussing the remaining challenges and perspectives for better use of nowadays detection methods in practical usage.
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Sameer, Venkata Udaya, Ruchira Naskar, Nikhita Musthyala, and Kalyan Kokkalla. "Deep Learning Based Counter–Forensic Image Classification for Camera Model Identification." In Digital Forensics and Watermarking, 52–64. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-64185-0_5.

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Yu, Jingjing, Yifeng Zhan, Jianhua Yang, and Xiangui Kang. "A Multi-purpose Image Counter-anti-forensic Method Using Convolutional Neural Networks." In Digital Forensics and Watermarking, 3–15. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-53465-7_1.

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Conference papers on the topic "Forensics and counter-forensics"

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Dang-Nguyen, D. T., I. D. Gebru, V. Conotter, G. Boato, and F. G. B. De Natale. "Counter-forensics of median filtering." In 2013 IEEE 15th International Workshop on Multimedia Signal Processing (MMSP). IEEE, 2013. http://dx.doi.org/10.1109/mmsp.2013.6659298.

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Iuliani, M., S. Rossetto, T. Bianchi, Alessia De Rosa, A. Piva, and M. Barni. "Image counter-forensics based on feature injection." In IS&T/SPIE Electronic Imaging, edited by Adnan M. Alattar, Nasir D. Memon, and Chad D. Heitzenrater. SPIE, 2014. http://dx.doi.org/10.1117/12.2042234.

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Goljan, Miroslav, Jessica Fridrich, and Mo Chen. "Sensor noise camera identification: countering counter-forensics." In IS&T/SPIE Electronic Imaging, edited by Nasir D. Memon, Jana Dittmann, Adnan M. Alattar, and Edward J. Delp III. SPIE, 2010. http://dx.doi.org/10.1117/12.839055.

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Fahmy, Gamal, Abdullah Alqallaf, and Rolf Wurtz. "Phase based detection of JPEG counter forensics." In 2015 IEEE International Conference on Electronics, Circuits, and Systems (ICECS). IEEE, 2015. http://dx.doi.org/10.1109/icecs.2015.7440243.

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Valenzise, G., M. Tagliasacchi, and S. Tubaro. "Detectability-quality trade-off in JPEG counter-forensics." In 2014 IEEE International Conference on Image Processing (ICIP). IEEE, 2014. http://dx.doi.org/10.1109/icip.2014.7026080.

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Marra, Francesco, Giovanni Poggi, Fabio Roli, Carlo Sansone, and Luisa Verdoliva. "Counter-forensics in machine learning based forgery detection." In IS&T/SPIE Electronic Imaging, edited by Adnan M. Alattar, Nasir D. Memon, and Chad D. Heitzenrater. SPIE, 2015. http://dx.doi.org/10.1117/12.2182173.

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Drescher, Adam, Brandon De Luna, Marjolein Pasman, Derek Haas, and Sheldon Landsberger. "Revamping of a Graduate Radiochemistry Course for Nuclear Forensics Applications." In 2018 26th International Conference on Nuclear Engineering. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/icone26-81593.

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Laboratories in traditional radiochemistry courses typically involve basic and fundamental understanding in solvent extraction, ion exchange, precipitation, etc. procedures. With the increased focus on nuclear forensics in pre- and post-detonation scenarios different skill sets are now required for the student to learn. At the University of Texas we have developed two independent graduate courses in gamma-ray spectrometry and radiochemistry. Currently, we have amalgamated these two courses to 1. better serve our nuclear engineering graduate students, many of which are involved in nuclear forensics and 2. to attract both undergraduate and graduate students from the Chemistry Department. We incorporated gamma-ray spectrometry laboratories with several others which are nuclear forensics related. The seven laboratory sessions include half-life measurement of 137mBa (the daughter produce of 137Cs) and secular equilibrium, basic gamma and beta shielding, and gamma-ray spectrometry calibration, resolution and uncertainty in statistics. These labs have been augmented with four others including uranium fission product identification, 137Cs soil profile with Compton suppression, tritium analysis in water with a liquid scintillation counter and double replacement reaction.
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DeLooze, Lori L. "Counter hack: Creating a context for a cyber forensics course." In 2008 IEEE Frontiers in Education Conference (FIE). IEEE, 2008. http://dx.doi.org/10.1109/fie.2008.4720283.

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Osakabe, Takayuki, Miki Tanaka, Yuma Kinoshita, and Hitoshi Kiya. "CycleGAN without checkerboard artifacts for counter-forensics of fake-image detection." In International Workshop on Advanced Image Technology 2021, edited by Wen-Nung Lie, Qian Kemao, Jae-Gon Kim, and Masayuki Nakajima. SPIE, 2021. http://dx.doi.org/10.1117/12.2590977.

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Raj, Aiswariya, and Deepa Sankar. "Counter Forensics: A New PRNU Based Method for Image Source Anonymization." In 2019 IEEE International Conference on Electrical, Computer and Communication Technologies (ICECCT). IEEE, 2019. http://dx.doi.org/10.1109/icecct.2019.8868948.

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