Abstract
Digital evidence collection and analysis have become an increasing tool to solve crimes and prepare courts’ cases over the last two decades, undergoing major changes in the area of IT. Crime is a major problem every day, so that computer forensics are avoided and protected from crime. More information is created, stored and accessed with increasingly portable and powerful technology. Mobile systems may serve as large personal knowledge archives in a wallet still accessible through a hand or phrase. The advantage is obvious by having ample information in order to obtain judgments, but the collection and admissibility of digital proof should be balanced with the privacy concerns of law enforcement and other parties to criminal law. The need of validating the honesty of digital video content ranges from a person to associations, obstacles and security arrangements to law authorization/organizations’. With video and image changing, the change tools have made it simple to modify media content. Therefore, it is necessary to investigate viable methods for video falsification.
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References
S. Li, Q. Sun, X. Xu, Forensic analysis of digital images over smart devices and online social networks. in 2018 IEEE 20th International Conference on High Performance Computing and Communications; IEEE 16th International Conference on Smart City; IEEE 4th International Conference on Data Science and Systems (HPCC/Smart City/DSS), June (2018), pp. 1015–1021
T. Gloe, A. Fischer, M. Kirchner, “Forensic analysis of video file formats”. digital ınvestigation. in Proceedings of the First Annual DFRWS Europe, vol. 11, (2014), pp. S68–S76
G. Horsman, Reconstructing streamed video content: a case study on youtube and facebook live stream content in the chrome web browser cache. Digit. Investig. 26, S30–S37 (2018)
S. Saikia, E. Fidalgo, E. Alegre, L. Fernández-Robles, Object detection for crime scene evidence analysis using deep learning, in Image Analysis and Processing—ICIAP 2017. ed. by S. Battiato, G. Gallo, R. Schettini, F. Stanco (Springer International Publishing, Cham, 2017), pp. 14–24
E.E. Kenneally, C.L.T. Brown, Risk sensitive digital evidence collection. Digital Investig. J. 2(2), (Elsevier, 2005)
G. Tzanidou, I. Zafar, E.A. Edirisinghe, Carried object detection in videos using color information. IEEE Trans. Inf. Forensics Secur. 8(10), 1620–1631 (2013)
C. Chuang, J. Hsieh, L. Tsai, S. Chen, K. Fan, Carried object detection using ratio histogram and its application to suspicious event analysis. IEEE Trans. Circuits Syst. Video Technol. 19(6), 911–916 (2009)
H. Farid, Digital doctoring: how to tell the real from fake. Significance 3(4), 162–166 (2006)
R.S. Ram, S.A. Prakash, M. Balaanand, C.B. Sivaparthipan, Colour and orientation of pixel based video retrieval using IHBM similarity measure. Multimedia Tools Appl. 79(15–16), 10199–10214 (2019). https://doi.org/10.1007/s11042-019-07805-9
T.N. Nguyen, B. Liu, N.P. Nguyen, J. Chou, Cyber security of smart grid: attacks and defenses. in ICC 2020–2020 IEEE International Conference on Communications (ICC), Dublin, Ireland (2020), pp. 1–6. https://doi.org/10.1109/ICC40277.2020.9148850
A. Rocha, W. Scheirer, T. Boult, S. Goldenstein, Vision of the unseen: current trends and challenges in digital image and video forensics. ACM Comput. Surv. 43(4), 26 (2011)
V. Joshi, S. Jain, Tampering detection in digital video e a review of temporal fingerprints based techniques. in Proceedings of 2nd International Conference on Computing for sustainable global development, New Delhi, India (2015), pp. 1121–1124
K.K. Sitara, B.M. Mehtre, Digital video tampering detection: an overview of passive techniques. Digit. Investig. 18, 8–22 (2016)
M.C. Stamm, M. Wu, K.J.R. Liu, Information forensics: an overview of the first decade. Access IEEE. 1, 167–200 (2013)
National Institute of Standards and Technology, Guidelines on mobile device forensics (draft), Special Publication 800–101. U.S. Department of Commerce, Gaithersburg, MD (2013)
S.E. Goodison, R.C. Davis, B.A. Jackson, in Digital evidence and the U.S. Criminal Justice System: Identifying Technology and Other Needs to More Effectively Acquire and Utilize Digital Evidence. (Santa Monica, CA: RAND Corporation, 2015)
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Yallamandhala, P., Godwin, J. (2022). A Review on Video Tampering Analysis and Digital Forensic. In: Manogaran, G., Shanthini, A., Vadivu, G. (eds) Proceedings of International Conference on Deep Learning, Computing and Intelligence. Advances in Intelligent Systems and Computing, vol 1396. Springer, Singapore. https://doi.org/10.1007/978-981-16-5652-1_24
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DOI: https://doi.org/10.1007/978-981-16-5652-1_24
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