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.

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