Qingzhong Liu
ABSTRACT
Image tampering, being widely facilitated and proliferated by today's digital techniques, is increasingly causing problems concerning the authenticity of digital images. As one of the most favorable compressed media, JPEG image can be easily tampered without leaving any visible clues. JPEG-based forensics, including the detection of double compression, interpolation, rotation, etc, has been actively performed. However, the detection of misaligned cropping and recompression, with the same quantization matrix that was once used to encode original JPEG images, has not been effectively expressed or ignored to some extent. Aiming to detect such manipulations for forensics purpose, in this paper, we propose an approach based on block artifacts caused by the manipulation with JPEG compression. Specifically, we propose a shift-recompression based detection method to identify the inconsistency of the block artifacts in doctored JPEG images. The learning classifiers are applied for classification. Experimental results show that our approach is very promising to detect misaligned cropping and recompression with the same quantization matrix and greatly improves the existing methods. Our detection method is also very effective to detect relevant copy-paste and composite forgery in JPEG images.
- http://www.npr.org/blogs/thetwo-way/2010/09/17/129938169/doctored-photograph-hosni-mubarak-al-ahram-white-house-obama-mideast-peace-talksGoogle Scholar
- Bayram S, Sencar HT and Memon N (2009). An efficient and robust method for detecting copy-move forgery. Proc. IEEE International Conference on Acoustics, Speech, and Signal Processing, April 19--24, 2009. Google ScholarDigital Library
- Chen W, Shi YQ and Su W (2007). Image splicing detection using 2-D phase congruency and statistical moments of characteristic function. Proc. SPIE, Vol. 6505, 65050R (2007); DOI:10.1117/12.704321.Google ScholarCross Ref
- Chen C, Shi YQ and Su W (2008). A machine learning based scheme for double JPEG compression detection. ICPR 2008: 1--4.Google ScholarCross Ref
- Chen Y and Hsu C (2011). Detecting recompression of JPEG images via periodicity analysis of compression artifacts for tampering detection. IEEE Transactions on Information Forensics and Security, 6(2): 396--406. Google ScholarDigital Library
- Dirik A E and Memon N (2009). Image tamper detection based on demosaicing artifacts. Proc. IEEE ICIP'09, November 2009. Google ScholarDigital Library
- Farid H (1999). Detecting digital forgeries using bispectral analysis. AI Lab, Massachusetts Institute of Technology, Tech. Rep. AIM-1657, 1999. Google ScholarDigital Library
- Farid H (2006). Digital image ballistics from JPEG quantization. Dept. Comput.Sci., Dartmouth College, Tech. Rep. TR2006--583, 2006.Google Scholar
- Farid H (2009). Image forgery detection, a survey. IEEE Singal Processing Magazine, March 2009, 16--25.Google Scholar
- Farid H (2009). Exposing digital forgeries from JPEG ghosts. IEEE Transactions on Information Forensics and Security, 4(1):154--160. Google ScholarDigital Library
- Fridrich J, Soukal D and Lukás J (2003). Detection of copy move forgery in digital images. Proc. Digital Forensic Research Workshop, Aug. 2003.Google Scholar
- Fridrich J (2004). Feature-based steganalysis for JPEG images and its implications for future design of steganographic schemes. Lecture Notes in Computer Science, 3200, 67--81. Google ScholarDigital Library
- Hilbe JM (2009). Logistic Regression Models. Chapman & Hall/CRC Press. ISBN 978--1--4200--7575--5.Google Scholar
- Huang F, Huang J and Shi Y (2010). Detecting double JPEG compression with the same quantization matrix. IEEE Transactions on Information Forensics and Security, 5(4):848--856. Google ScholarDigital Library
- Joachims T (2000). Estimating the generalization performance of a SVM efficiently. Proc. of the International Conference on Machine Learning, Morgan Kaufman, 2000. Google ScholarDigital Library
- Kodovsky J and Fridrich J (2009). Calibration revisited. Proceedings of the 11th ACM Multimedia and Security Workshop, Princeton, NJ, September 7--8, 2009. Google ScholarDigital Library
- Kirchner M (2008). Fast and reliable resampling detection by spectral analysis of fixed linear predictor residue. Proc. 10th ACM Multimedia and Security Workshop, pp. 11--20. Google ScholarDigital Library
- Liu Q, Sung AH and Qiao M (2009). Improved detection and evaluation for JPEG steganalysis. Proc. ACM Multimedia 2009, 873--876. Google ScholarDigital Library
- Liu Q, Sung AH and Qiao M (2009). Novel stream mining for audio steganalysis. Proc. 17th ACM Multimedia, pp. 95--104, 2009. Google ScholarDigital Library
- Liu Q, Sung A H and Qiao M (2009). Temporal derivative based spectrum and mel-cepstrum audio steganalysis. IEEE Transactions on Information Forensics and Security, 4, 3, 359--368. Google ScholarDigital Library
- Liu Q and Sung AH (2009). A new approach for JPEG resize and image splicing detection. Proc. ACM Multimedia Workshop on Multimedia in Forensics 2009, pp. 43--47. Google ScholarDigital Library
- Liu Q, Sung AH and Qiao M (2011). A method to detect JPEG-based double compression. In Proc. of 8th International Symposium on Neural Networks, pp 466--476. Google ScholarDigital Library
- Liu Q, Sung AH and Qiao M (2011). Neighboring joint density based JPEG steganalysis. ACM Transactions on Intelligent Systems and Technology, 2(2), 16:1--16. Google ScholarDigital Library
- Liu Q, Sung AH and Qiao M (2011). Derivative based audio steganalysis. ACM Transactions on Multimedia Computing, Communications and Application, 7(3), 18:1--19. Google ScholarDigital Library
- Liu Q (2011). Steganalysis of DCT-Embedding-based Adaptive Steganography and YASS, Proc. 13th ACM Workshop on Multimedia and Security, September 28--29, 2011, Buffalo, NY. Google ScholarDigital Library
- Luo W, Qu Z, Huang J and Qiu G (2007). A novel method for detecting cropped and recompressed image block. Proc. IEEE Conf. Acoustics, Speech and Signal Processing 2007, pp. 217--220.Google ScholarCross Ref
- Pan X and Lyu S (2010). Region duplication detection using image feature matching. IEEE Trans. on Info. Forensics and Security, 5(4):857--867. Google ScholarDigital Library
- Pevny T and Fridrich J (2008). Detection of double-compression in JPEG images for applications in steganography. IEEE Trans. Information Forensics and Security, 3(2):247--258, 2008. Google ScholarDigital Library
- Popescu AC and Farid H (2004). Statistical tools for digital forensics. Proc. 6th Int. Workshop on Information Hiding, pp. 128--147. Google ScholarDigital Library
- Popescu AC and Farid H (2005). Exposing digital forgeries by detecting traces of re-sampling. IEEE Trans. Signal Processing 53(2): 758--767. Google ScholarDigital Library
- Popescu AC and Farid H (2005). Exposing digital forgeries in color filter array interpolated images. IEEE Trans. Signal Processing 53(10): 3948--3959. Google ScholarDigital Library
- Prasad S and Ramakrishnan KR (2006). On resampling detection and its application to image tampering. Proc. IEEE Int. Conf. Multimedia and Exposition 2006, pp. 1325--1328.Google ScholarCross Ref
- Shi YQ, Chen C and Chen W (2007). A Markov process based approach to effective attacking JPEG steganography. Lecture Notes in Computer Science, vol.4437, pp. 249--264. Google ScholarDigital Library
- Vapnik, V. 1998. Statistical Learning Theory, John Wiley, 1998.Google ScholarDigital Library
- http://www.csie.ntu.edu.tw/~cjlin/libsvm/Google Scholar
Index Terms
- Detection of misaligned cropping and recompression with the same quantization matrix and relevant forgery
Recommendations
Self-embedding fragile watermarking scheme to restoration of a tampered image using AMBTC
The problem of digital forgeries has become more and more serious in various fields like entertainment, digital forensics, and journalism. This paper proposes a self-embedding watermarking scheme for the restoration of an image after tampering by ...
Shift recompression-based feature mining for detecting content-aware scaled forgery in JPEG images
MDMKDD '12: Proceedings of the Twelfth International Workshop on Multimedia Data MiningContent-aware image resizing, also known as image retargeting, seam carving, content-aware scaling, is originally proposed to automatically remove the paths of least importance, known as seams, to reduce image size or insert seams to extend it, in order ...
A Fast Image Copy-Move Forgery Detection Method Using Phase Correlation
MINES '12: Proceedings of the 2012 Fourth International Conference on Multimedia Information Networking and SecurityCopy-move is a common used forgeries in digital image tampering. In this paper, a non block-matching based fast method to detect image copy-move forgery is proposed exploiting phase correlation. Results of experiments indicate that the proposed method ...
Comments