An improved anti-forensics JPEG compression using Least Cuckoo Search algorithm

References

• Lanh TV, Chong K-S, Emmanuel S, et al. A survey on digital camera image forensic methods. Proceedings of IEEE International Conference on Multimedia and Expo; 2007, p. 16–19.
   Google Scholar
• Mahdian B, Saic S. A bibliography on blind methods for identifying image forgery. Signal Process Image Commun. 2010;25(6):389–399. doi: 10.1016/j.image.2010.05.003
   Web of Science ®Google Scholar
• Farid H. A survey of image forgery detection. IEEE Signal Process Mag. 2009;26(2):16–25. doi: 10.1109/MSP.2008.931079
   Web of Science ®Google Scholar
• Birajdar GK, Mankar VH. Digital image forgery detection using passive techniques: a survey. Digit Invest. 2013;10(3):226–245. doi: 10.1016/j.diin.2013.04.007
   Web of Science ®Google Scholar
• Qian Z, Zhang X. Improved anti-forensics of JPEG compression. J Syst Softw. 2014;91:100–108. doi: 10.1016/j.jss.2013.12.043
   Web of Science ®Google Scholar
• Popescu AC, Farid H. Statistical tools for digital forensics. Proceedings of 6th International Workshop on Information Hiding; Toronto, Canada; 2004.
   Google Scholar
• Ye S, Sun Q, Chang E-C. Detecting digital image forgeries by measuring inconsistencies of blocking artifact. Proceedings of IEEE International Conference on Multimedia and Expo; 2007. p. 12–15.
   Google Scholar
• Li H, Luo W, Huang J. Countering anti-JPEG compression forensics. Proceedings of 19th IEEE International Conference on Image Processing; 2012. p. 241–244.
   Google Scholar
• Fan Z, De Queiroz RL. Identification of bitmap compression history: JPEG detection and quantizer estimation. IEEE Trans Image Process. 2003;12(2):230–235. doi: 10.1109/TIP.2002.807361
   PubMed Web of Science ®Google Scholar
• Böhme R, Kirchner M. Counter-forensics: attacking image forensics. In: Sencar HT, Memon N, editors. Digital image forensics. New York, NY: Springer; 2013. p. 327–366.
   Google Scholar
• Singh G, Singh K. Improved JPEG anti-forensics with better image visual quality and forensic undetectability. Forensic Sci. Int. 2017;277:133–147. doi: 10.1016/j.forsciint.2017.06.003
   PubMed Web of Science ®Google Scholar
• Pasquini C, Boato G. JPEG compression anti-forensics based on first significant digit distribution. Proceedings of the IEEE 15th International Workshop on Multimedia Signal Processing (MMSP); 2013.
   Google Scholar
• Valenzise G, Tagliasacchi M, Tubaro S. Revealing the traces of JPEG compression anti-forensics. IEEE Trans Inf Forensics Secur. 2013;8(2):335–349. doi: 10.1109/TIFS.2012.2234117
   Web of Science ®Google Scholar
• Zeng H, Qin T, Kang X, et al. Countering anti-forensics of median filtering. Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP); 2014. p. 2704–2708.
   Google Scholar
• Kirchner M, Boehme R. Synthesis of colour filter array pattern in digital images). Proceedings of SPIE Media Forensics and Security; 2009.
   Google Scholar
• Barni M, Fontani M, Tondi B. A universal technique to hide traces of histogram-based image manipulations. Proceedings of Multimedia and Security; 2012. p. 97–104.
   Google Scholar
• Yang X-S, Deb S. Cuckoo search via levy flights. World Congress on Nature & Biologically Inspired Computing; 2009. p. 210–214.
   Google Scholar
• Kwong RH, Johnston EW. A variable step size LMS algorithm. IEEE Trans Signal Process. 1992;40(7):1633–1642. doi: 10.1109/78.143435
   Web of Science ®Google Scholar
• Li H, Luo W, Huang J. Anti-forensics of double JPEG compression with the same quantization matrix. Multimed Tools Appl. 2015;74(17):6729–6744. doi: 10.1007/s11042-014-1927-0
   Web of Science ®Google Scholar
• Li Y, Zhou J. Anti-Forensics of lossy predictive image compression. IEEE Signal Process Lett. 2015;22(12):2219–2223. doi: 10.1109/LSP.2015.2472561
   Web of Science ®Google Scholar
• Fan W, Wang K, Cayre F, et al. JPEG Anti-Forensics with improved tradeoff between forensic undetectability and image quality. IEEE Trans Inf Forensics Secur. 2014;9(8):1211–1226. doi: 10.1109/TIFS.2014.2317949
   Web of Science ®Google Scholar
• Stamm MC, Ray Liu KJ. Anti-Forensics of digital image compression. IEEE Trans Inf Forensics Secur. 2011;6(3):1050–1065. doi: 10.1109/TIFS.2011.2119314
   Web of Science ®Google Scholar
• Fan W, Wang K, Cayre F, et al. Median filtered image quality enhancement and anti-forensics via variational de-convolution. IEEE Trans Inf Forensics Secur. 2015;10(5):1076–1091. doi: 10.1109/TIFS.2015.2398362
   Web of Science ®Google Scholar
• Chu X, Stamm MC, Chen Y, et al. On anti-forensic concealability with rate-distortion tradeoff. IEEE Trans Image Process. 2015;24(3):1087–1100. doi: 10.1109/TIP.2015.2390137
   PubMed Web of Science ®Google Scholar
• Chen C, Li H, Luo W, et al. Anti-forensics of JPEG detectors via adaptive quantization table replacement. Proceedings of IEEE International Conference on Pattern Recognition; 2014, p. 672–677.
   Google Scholar
• Yadav P. Adaptive firefly optimization on reducing high dimensional weighted word affinity graph. Int J Comput Sci Eng Technol. 2014;3(12):1407–1411.
   Google Scholar
• Valenzise G, Nobile V, Tagliasacchi M, et al. Countering JPEG anti-forensics. Proceedings of 18th IEEE International Conference on Image Processing; Brussels; 2011. p. 1949–1952.
   Google Scholar
• Pennebaker B, Mitchell L. JPEG still image data compression standard. New York (NY): Van Nostrand Reinhold; 1993.
   Google Scholar
• Lai S, Böhme R. Countering counter-forensics: The case of JPEG compression. Proc. Int. Conf. Inf. Hiding; 2011. p. 285–298.
   Google Scholar
• http://homepages.lboro.ac.uk/~cogs/datasets/ucid/ucid.html. Since this research was conducted, the Cogs image dataset repository has been removed. The authors have retained this web address link to show where the images used in Figure 5 were obtained, and to credit the repository accordingly.
   Google Scholar