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B-Frames: Efficiency Analysis for Digital Video Tampering Detection in Videos with Variable GOP Structure

V.Joshi 1 , S. Jain2 , C. Bansal3

  1. SOCA, ITM University, Gwalior, India.
  2. SOCA, ITM University, Gwalior, India.
  3. MCA, BVICAM, GGSIPU, New Delhi, India.

Section:Research Paper, Product Type: Journal Paper
Volume-6 , Issue-5 , Page no. 808-815, May-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i5.808815

Online published on May 31, 2018

Copyright © V.Joshi, S. Jain, C. Bansal . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: V.Joshi, S. Jain, C. Bansal, “B-Frames: Efficiency Analysis for Digital Video Tampering Detection in Videos with Variable GOP Structure,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.5, pp.808-815, 2018.

MLA Style Citation: V.Joshi, S. Jain, C. Bansal "B-Frames: Efficiency Analysis for Digital Video Tampering Detection in Videos with Variable GOP Structure." International Journal of Computer Sciences and Engineering 6.5 (2018): 808-815.

APA Style Citation: V.Joshi, S. Jain, C. Bansal, (2018). B-Frames: Efficiency Analysis for Digital Video Tampering Detection in Videos with Variable GOP Structure. International Journal of Computer Sciences and Engineering, 6(5), 808-815.

BibTex Style Citation:
@article{Jain_2018,
author = {V.Joshi, S. Jain, C. Bansal},
title = {B-Frames: Efficiency Analysis for Digital Video Tampering Detection in Videos with Variable GOP Structure},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {5 2018},
volume = {6},
Issue = {5},
month = {5},
year = {2018},
issn = {2347-2693},
pages = {808-815},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=2068},
doi = {https://doi.org/10.26438/ijcse/v6i5.808815}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i5.808815}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=2068
TI - B-Frames: Efficiency Analysis for Digital Video Tampering Detection in Videos with Variable GOP Structure
T2 - International Journal of Computer Sciences and Engineering
AU - V.Joshi, S. Jain, C. Bansal
PY - 2018
DA - 2018/05/31
PB - IJCSE, Indore, INDIA
SP - 808-815
IS - 5
VL - 6
SN - 2347-2693
ER -

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Abstract

Digital video tampering is an act of malicious modification of video content. This could be done to hide or cover an object or to alter the meaning conveyed by the digital video. The research performed is summarized in this paper by analyzing various inter frame forgery detection approaches for digital video, proposed so far, highlighting the strengths and weaknesses of each approach discussed. All approaches proposed so far are making use of P-frames for forgery detection. Comparison of P-frames and B-frames has been performed in terms of complexity and accuracy of algorithms developed using each of them. All the way through the research performed, authors tried to access the worth of B-frames in digital video forgery detection.

Key-Words / Index Term

Video Forgery Detection, Group of Pictures (GOP), B-frames, Video tampering, Intra Frame, Predicted Frame, Bi-directional frames, High efficiency video coding

References

[1]. B.G. Haskell and A. Puri: MPEG Video Compression Basics, Chapter 2. In:L. Chiariglione (ed.), The MPEG Representation of Digital Media, DOI 10.1007/978-1-4419-6184-6_2, © Springer Science+Business Media, LLC 2012.
[2]. I. Amerini, R. Becarelli, R. Caldelli, and M. Casini. A feature-based forensic procedure for splicing forgeries. Mathematical problems in Engineering, 2015
[3]. W. Wong and H. Farid “Exposing Digital Forgeries in video by detecting double quantization” Proceeding of MM& SEC 2009, ACM 978-1-59593-857-2/07/0009
[4]. Salam A.Thajeel and Ghazali Bin Sulong:State of the art of copy-move forgery detection techniques: a review. In: IJCSI International Journal of Computer Science Issues, Vol. 10, Issue 6, No 2, November 2013.
[5]. Sowmya K.N., H.R. Chennamma: A survey on video forgery detection. In: International Journal of Computer Engineering and Applications, Volume IX, Issue II, February 2015.
[6]. C. Cruz-Ramos, R. Reyes-Reyes, M. Nakano-Miyatake, H. Perez-Meana: A Blind Video Watermarking Scheme Robust to Frame Attacks Combined with MPEG2 Compression. In: Journal of Applied Research and Technology, Vol. 8, No. 3, December 2010.
[7]. Staffy Kingra, Naveen Aggarwal and Raahat Devender Singh: Video Inter-frame Forgery Detection: A Survey. In: Indian Journal of Scienceand Technology, Vol 9(44), DOI: 10.17485/ijst/2016/v9i44/105142, November 2016.
[8]. Ainuddin Wahid Abdul Wahab, Mustapha Aminu Bagiwa, Mohd Yamani Idna Idris, Suleman Khan and Zaidi Razak: Passive Video Forgery Detection Techniques: A Survey. In: 2014 International Conference on Information Assurance and Security (IAS).
[9]. Tanzeela Qazi, Khizar Hayat, Samee U. Khan, Sajjad A. Madani, Imran A. Khan,Joanna Kołodziej, Hongxiang Li, Weiyao Lin, Kin Choong Yow and Cheng-Zhong Xu: Survey on blind image forgery detection. In: in IET Image Processing, Accepted on 19th February 2013 doi:10.1049/iet-ipr.2012.0388.
[10]. D. Labartino, T.Bianchi, A. De Rosa, M. Fontani, D. V´azquez-Pad,A. Piva, M. Barni, “Localization of Forgeries in MPEG-2 Videothrough GOP Size and DQ Analysis” MMSP’13, Sept. 30 - Oct. 2, 2013, Pula (Sardinia), Italy.
[11]. Umesh Kumar Singh, Chanchala Joshi, Suyash Kumar Singh, "Zero day Attacks Defense Technique for Protecting System against Unknown Vulnerabilities", International Journal of Scientific Research in Computer Science and Engineering, Vol.5, Issue.1, pp.13-18, 2017Su, Y., Zhang, J., Liu, J.: Exposing digital video forgery by detecting motion-compensated edge artifact. In: Proceedings of International Conference on Computational Intelligence and Software Engineering, Wuhan, China. Vol. 1, no. 4, pp. 11–13 (2009).
[12]. Qiong Dong, Gaobo Yang, Ningbo Zhu: A MCEA based passive forensics scheme for detecting frame-based video tampering. In: Digital Investigation, November 2012, DOI:0.1016/j.diin.2012.07.002
[13]. Raahat Devender Singh and Naveen Aggarwal: Video content authentication techniques: a comprehensive survey. In: 19 January 2017 © Springer-Verlag Berlin Heidelberg 2017.
[14]. Huang, Xinyi, and Jianying Zhou, eds. Information Security Practice and Experience: 10th International Conference, ISPEC 2014, Fuzhou, China, May 5-8, 2014, Proceedings. Vol. 8434. Springer, 2014.
[15]. Javad Abbasi Aghamaleki& Alireza Behrad: Malicious inter-frame video tampering detection in MPEG videos using time and spatial domain analysis of quantization effects. In: Springer Science+Business Media New York 2016, Accepted: 23 September 2016.
[16]. Jingxian Liu and Xiangui Kang: Exposing Heterogeneous Chain of Video Recompression. In: Guangdong Key Lab of Information Security, School of Data and Computer Science, Sun Yat-Sen University, Guangzhou 510006, China.
[17]. Vázquez-Padín, D., Fontani, M., Bianchi, T., Comesana, P., Piva, A. Barni, M.: Detection of video double encoding with GOP size estimation. In: Proceedings on IEEE International Workshop on Information Forensics and Security, Tenerife, Spain, 151 (2012)
[18]. Hee-Meng, Ho: ‘Digital Video Forensics: Detecting MPEG-2 Video Tampering through Motion Errors’. In: MSc. Information Security 2011/12, Royal Holloway University of London.
[19]. A. Gironi, M. Fontani, T. Bianchi, A. Piva, M. Barni (2014). A video forensic technique for detecting frame deletion and insertion. In: 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Firenze, May 2014. pp. 6226-6230.
[20]. Xin-Wei Yao, Yue-Feng Cen, Wan-Liang Wang, Xiao-Min Yao, Shuang-Hua Yang and Tie-Qiang Pan: IPB-frame Adaptive Mapping Mechanism for Video Transmission over IEEE 802.11e WLAN. In: ACM SIGCOMM Computer Communication Review, Volume 44, Number 2, April 2014.
[21]. Jianmei Yang & Tianqiang Huang & Lichao Su: Using similarity analysis to detect frame duplication forgery in videos.In: Published online-20 November 2014, Springer Science+Business Media New York 2014.
[22]. A.V. Subramanyam and Sabu Emmanuel: Pixel Estimation Based Video Forgery Detection. In:Acoustics, Speech and Signal Processing, 1988. ICASSP-88., 1988InternationalConference on October 2013.
[23]. Lichao Su & Tianqiang Huang & Jianmei Yang: Avideo forgery detection algorithm based on compressive sensing. In: Springer Science+Business Media New York 2014, 2 March 2014.
[24]. Jianmei Yang & Tianqiang Huang & Lichao Su: Using similarity analysis to detect frame duplication forgery in videos. In: Springer Science+Business Media New York 2014, Published online: 20 November 2014.
[25]. Liyang Yu•Qi Han•Xiamu Niu: Feature point-based copy-move forgery detection: covering the non-textured areas. In: Published online: 4 December 2014 at Springer Science+Business Media New York 2014.
[26]. Mohammad Jafari, Neda Abdollahi, Ali Amiri, Mahmood Fathy, "Generalization of Determinant Kernels for Non-Square Matrix and its Application in Video Retrieval", International Journal of Scientific Research in Computer Science and Engineering, Vol.3, Issue.4, pp.1-6, 2015
[27]. Ashish Kumar Kushwaha and Avinash Wadhe: Design and Implementation of Forensic Framework for Video Forensics. In: International Journal of Current Engineering and Technology, Accepted 02 April 2015, Available online 07 April 2015, Vol.5, No.2 (April 2015).
[28]. D. V´azquez-Pad´ın, M. Fontani, T. Bianchi, P. Comesa˜na, A. Piva, M. Barni: Detection of video double encoding with GOP size estimation. In: WIFS‘2012, December, 2-5, 2012, Tenerife, Spain. 978-14244-9080-6/10/$26.00 copyrights-2012 IEEE.
[29]. Markus Flierland Bernd Girod: Generalized B Pictures and the Draft H.264/AVC Video Compression Standard. In: IEEE Transactions on circuits and systems for video technology.
[30]. Bruno Zatt, Marcelo Porto, Jacob Scharcanski, Sergio Bampi: GOP structure adaptive to the video content for efficient H.264/AVC encoding. In Proceedings of ICIP International Conference on Image Processing, September2010.
[31]. Nikhilkumar P. Joglekar1, Dr. P.N. Chatur: A Compressive Survey on Active and Passive Methods for Image Forgery Detection. In: International Journal Of Engineering And Computer Science ISSN:2319-7242 Volume 4 Issue 1 January 2015, Page No. 10187-10190.
[32]. Harmanpreet Kaur and Manpreet Kaur: Inter frame Video Duplication Forgery Detection: A Review. In: International Journal Of Engineering And Computer Science ISSN: 2319-7242 Volume 4 Issue 8 Aug 2015, Page No. 13806-13809.
[33]. Aldrina Christian, Ravi Sheth: Digital Video Forgery Detection and Authentication Technique - A Review. In: 2016 IJSRST | Volume 2 | Issue 6 | Print ISSN: 2395-6011 | Online ISSN: 2395-602X.