Development of photo forensics algorithm by detecting photoshop manipulation using error level analysis

Nowadays, image manipulation is common due to the availability of image processing software, such as Adobe Photoshop or GIMP. The original image captured by digital camera or smartphone normally is saved in the JPEG format due to its popularity. JPEG algorithm works on image grids, compressed independently, having size of 8x8 pixels. For unmodified image, all 8x8 grids should have a similar error level. For resaving operation, each block should degrade at approximately the same rate due to the introduction of similar amount of errors across the entire image. For modified image, the altered blocks should have higher error potential compred to the remaining part of the image. The objective of this paper is to develop a photo forensics algorithm which can detect any photo manipulation. The error level analysis (ELA) was further enhanced using vertical and horizontal histograms of ELA image to pinpoint the exact location of modification. Results showed that our proposed algorithm could identify successfully the modified image as well as showing the exact location of modifications.

[1]  Jiwu Huang,et al.  Improved Tampering Localization in Digital Image Forensics Based on Maximal Entropy Random Walk , 2016, IEEE Signal Processing Letters.

[2]  Jiwu Huang,et al.  JPEG Error Analysis and Its Applications to Digital Image Forensics , 2010, IEEE Transactions on Information Forensics and Security.

[3]  Jiantao Zhou,et al.  Anti-Forensics of Lossy Predictive Image Compression , 2015, IEEE Signal Processing Letters.

[4]  N. Krawetz A Picture ’ s Worth . . . Digital Image Analysis and Forensics Version 2 , 2007 .

[5]  Gregory K. Wallace,et al.  The JPEG still picture compression standard , 1991, CACM.

[6]  Fouad Khelifi,et al.  On the SPN Estimation in Image Forensics: A Systematic Empirical Evaluation , 2017, IEEE Transactions on Information Forensics and Security.

[7]  Nova Scotia,et al.  Faking It: Manipulated Photography before Photoshop , 2013 .

[8]  Florent Retraint,et al.  JPEG Quantization Step Estimation and Its Applications to Digital Image Forensics , 2017, IEEE Transactions on Information Forensics and Security.

[9]  Patrick de Smet,et al.  JPGcarve: An Advanced Tool for Automated Recovery of Fragmented JPEG Files , 2016, IEEE Transactions on Information Forensics and Security.

[10]  Zhang Xiong,et al.  JPEG Anti-Forensics With Improved Tradeoff Between Forensic Undetectability and Image Quality , 2014, IEEE Transactions on Information Forensics and Security.

[11]  Ainuddin Wahid Abdul Wahab,et al.  An evaluation of Error Level Analysis in image forensics , 2015, 2015 5th IEEE International Conference on System Engineering and Technology (ICSET).

[12]  Hongying Jin,et al.  Research of Blind Forensics Algorithm on Digital Image Tampering , 2014 .

[13]  Fernando Pérez-González,et al.  Forensic Detection of Processing Operator Chains: Recovering the History of Filtered JPEG Images , 2015, IEEE Transactions on Information Forensics and Security.

[14]  S. P. Ghrera,et al.  Pixel-Based Image Forgery Detection: A Review , 2014 .

[15]  Tiegang Gao,et al.  A robust detection algorithm for copy-move forgery in digital images. , 2012, Forensic science international.

[16]  Hai-Dong Yuan,et al.  Blind Forensics of Median Filtering in Digital Images , 2011, IEEE Transactions on Information Forensics and Security.

[17]  Yao Zhao,et al.  Contrast Enhancement-Based Forensics in Digital Images , 2014, IEEE Transactions on Information Forensics and Security.