Multiple Heterogeneous JPEG Image Hierarchical Forensic
Since image processing software is widely used to tamper or embed data into JPEG images, the forensics of tampered JPEG images now plays a considerable important role. However, most existing forensics methods that use binary classification can hardly deal with multiclass image forensics problems properly under network environments. In this paper, we propose a hierarchical forensics scheme against multiple heterogeneous JPEG images. We introduce a compression identifier based on Markov model of DCT coefficients as the first hierarchical section and then develop a tampering detection and steganalyzer separately as the second phase. We conduct a series of experiments to testify the validity of the proposed method.
KeywordsImage forensics Heterogeneous images Classification
The work is supported by the Foundation for Innovative Research Groups of the NSFC(Grant No. 71421001), NSFC (Grant No. 61172109).
- 1.Alessandro P (2013) An overview on image forensics. ISRN Sig ProcGoogle Scholar
- 6.Chen CH, Shi YQ, Su W (2008) A machine learning based scheme for double JPEG compression detection,” In: 19th international conference on pattern recognition, pp 1–4Google Scholar
- 7.Pevný T, Fridrich J (2007) Merging Markov and DCT features for multi-class JPEG steganalysis. In: Proceedings SPIE security, steganography, and watermarking of multimedia contents, San Jose, CA, vol 6505, pp 1–13Google Scholar
- 8.Fridrich J (2005) Feature-based steganalysis for JPEG images and its implications for future design of steganographic schemes. In: Fridrich J (ed) Information hiding, 6th international workshop, volume 3200 of lecture notes in computer science, pp 67–81Google Scholar
- 9.Fu D, Shi YQ, Su W (2007) A generalized Benford’s law for JPEG coefficients and its applications in image forensics. In: Proceedings of SPIE conference on electronic imaging, security and watermarking of multimedia contents, San Jose, USAGoogle Scholar
- 10.Li B, Shi YQ, Huang JW (2008) Detecting doubly compressed JPEG images by using mode based first digit features. In: IEEE international workshop on multimedia signal processing, pp 730–735Google Scholar
- 11.Chang CC, Lin CJ (2001) LIBSVM: a library for support vector machines, 2001. http://www.csie.ntu.edu.tw/~cjlin/libsvm
- 12.Provos N (2001) Defending against statistical steganalysis. In: 10th USENIX security symposium, Washington, D.C., pp 323–336Google Scholar
- 13.Westfeld A (2001) F5-a steganographic algorithm: high capacity despite better steganalysis. In: Proceedings of international workshop information hiding (IWIH), Pittsburgh, PA, pp 289–302Google Scholar
- 15.Holub V, Fridrich J (2014) Low complexity features for JPEG steganalysis using undecimated DCT. IEEE Trans Inf Forensics Secur 10(2):219–28Google Scholar