Bibliografias temáticas / Forensics and counter-forensics

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Literatura científica selecionada sobre o tema "Forensics and counter-forensics"

Autor: Grafiati
Publicado: 14 de março de 2023
Última modificação: 31 de julho de 2025

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Artigos de revistas sobre o assunto "Forensics and counter-forensics"

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Premanand Narasimhan and Dr. N. Kala. "Emerging Trends in Digital Forensics : Investigating Cybercrime." International Journal of Scientific Research in Computer Science, Engineering and Information Technology 11, no. 1 (2025): 3645–52. https://doi.org/10.32628/cseit251451.

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Digital forensics is a rapidly evolving field that plays a critical role in investigating cybercrime, data breaches, and illicit activities across various domains, including blockchain, cryptocurrency, and the dark web. This paper explores key areas of digital forensics, including computer forensics, mobile forensics, network forensics, cloud forensics, IoT forensics, and embedded system forensics. Emerging trends such as drone and satellite forensics highlight the increasing scope of forensic investigations beyond traditional computing environments. Additionally, the study delves into blockch
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DOVHAN, O., and T. TKACHUK. "Combating counter-forensics as a component of digital security of critical infrastructure of Ukraine." INFORMATION AND LAW, no. 2(53) (June 24, 2025): 115–25. https://doi.org/10.37750/2616-6798.2025.2(53).334135.

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The article examines counter-forensics as one of the most dangerous forms of digital interference, which poses a direct threat to the digital security of critical infrastructure of Ukraine in the conditions of a full-scale war. It is substantiated that counter-forensic technologies — including wiping, fileless attacks, steganography, deepfakes, and other tools designed to conceal digital traces — are actively employed in contemporary cyberattacks targeting the stability of critical elements of state infrastructure. The paper provides an interdisciplinary analysis of the technical, legal and or
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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 (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 (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 g
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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 universi
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Amit, Kapoor, and Vinod Mahor Prof. "Broadcasting Forensics Using Machine Learning Approaches." International Journal of Trend in Scientific Research and Development 7, no. 3 (2023): 1034–45. https://doi.org/10.5281/zenodo.8068297.

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Broadcasting forensic is the practice of using scientific methods and techniques to analyse and authenticate Multimedia content. Over the past decade, consumer-grade imaging sensors have become increasingly prevalent, generating vast quantities of images and videos that are used for various public and private communication purposes. Such applications include publicity, advocacy, disinformation, and deception, among others. This paper aims to develop tools that can extract knowledge from these visuals and comprehend their provenance. However, many images and videos undergo modification and mani
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Ahmed, Abdulghani Ali, Khalid Farhan, Waheb A. Jabbar, Abdulaleem Al-Othmani, and Abdullahi Gara Abdulrahman. "IoT Forensics: Current Perspectives and Future Directions." Sensors 24, no. 16 (2024): 5210. http://dx.doi.org/10.3390/s24165210.

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The Internet of Things forensics is a specialised field within digital forensics that focuses on the identification of security incidents, as well as the collection and analysis of evidence with the aim of preventing future attacks on IoT networks. IoT forensics differs from other digital forensic fields due to the unique characteristics of IoT devices, such as limited processing power and connectivity. Although numerous studies are available on IoT forensics, the field is rapidly evolving, and comprehensive surveys are needed to keep up with new developments, emerging threats, and evolving be
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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 (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 entailment
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Imeri Saiti, Deshira, Mentor Hamiti, and Jehona Asani. "Handling Data Security in Education." International Journal of Education & Well-Being 2, no. 2 (2024): 108–22. https://doi.org/10.62416/ijwb-41.

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Digital forensics is a new science and follows the rapid changes in the computer environment, expanding into many disciplines, which turns it into a very challenging field that requires the continuous development of methodologies and tools to counter the ever-newer changes in cybercrime. The research subject refers to the analysis and challenges of digital forensics, tracking of hard drives, recovery of deleted files from the hard drive, their quality after recovery, and the possibility of creating forensic images on physically damaged hard drives. The research is based on digital forensics an
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Mais fontes

Teses / dissertações sobre o assunto "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, multi
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Dafale, Ninad N. "Source Anonymization Through Counter Forensics." Thesis, 2017. http://ethesis.nitrkl.ac.in/9074/1/2017_MT_NNDafale.pdf.

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A lot of photographers and human rights advocates need to hide their identity while sharing their images on the internet. Hence, source–anonymization of digital images has become a critical issue in the present digital age. The art and science of impeding and misleading forensic analysis of the digital image is known as Counter Forensics. The current literature contains a number of digital forensic techniques for “source–identification” of digital images, one of the most efficient of them being Photo–Response Non–Uniformity (PRNU) sensor noise pattern based source detection. PRNU noise pattern
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Livros sobre o assunto "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 genuine
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Capítulos de livros sobre o assunto "Forensics and counter-forensics"

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Rodger, Johnny. "Counter-forensics." In Key Essays. 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. 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. 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. 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. 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. 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. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-68780-9_34.

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Ivascu, Lacramioara Nicoleta, and Hamid Jahankhani. "An Investigation into Counter Drones Digital Forensics Aided by Remote Identification." In Space Governance. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-62228-1_7.

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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. 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
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Das, Debjit, Banalata Bhunia, Ruchira Naskar, and Rajat Subhra Chakraborty. "Linear and Non-Linear Filter-based Counter-Forensics Against Image Splicing Detection." In Communications in Computer and Information Science. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-31407-0_20.

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Trabalhos de conferências sobre o assunto "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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Singamsetty, Ramu, Koneru Sai Chandra Has, Sravani Kukkapalli, Veera Narayana Mannipudi, K. V. D. Kiran, and A. V. Praveen Krishna. "Information Security Using Counter-Anti-Forensics." In 2023 9th International Conference on Advanced Computing and Communication Systems (ICACCS). IEEE, 2023. http://dx.doi.org/10.1109/icaccs57279.2023.10112678.

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Tailanián, Matías, Marina Gardella, Alvaro Pardo, and Pablo Musé. "Diffusion models meet image counter-forensics." In 2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). IEEE, 2024. http://dx.doi.org/10.1109/wacv57701.2024.00388.

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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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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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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 foren
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Relatórios de organizações sobre o assunto "Forensics and counter-forensics"

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Naif Arab University for Security Sciences, Centre of Excellence in Cybercrimes and Digital Forensics. Cyber-enabled Terrorism in the African and Arab Regions: Survey Report from NAUSS-UNCCT Workshop. Naif University Press, 2024. http://dx.doi.org/10.26735/iwjx5145.

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The seventh review of the United Nations Global Counter-Terrorism Strategy (A/RES/75/291) underscored Member States' deep concern regarding the use of the Internet and other technologies for terrorist activities. Emphasizing collaboration among academia, the private sector, and civil society, the resolution sought to prevent terrorists from finding safe haven online while promoting an open, secure, and innovative Internet. In alignment with these principles, the Centre of Excellence in Cybercrimes and Digital Forensics (CoECDF) at Naif Arab University for Security Sciences (NAUSS) and UNOCT's
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