The game of countering JPEG anti-forensics based on the noise level estimation

It´s well known that JPEG image compression can result in quantization artifacts and blocking artifacts. There are plenty of forensic techniques making use of image´s compression fingerprints to verify digital images. However, when a forger exists, these methods are not reliable any more. One typical anti-forensic method is adding anti-forensic dither to DCT transform coefficients and erasing blocking artifacts to remove compression history. In this paper, we propose a new countering anti-forensic method based on estimating the noise added in the process of erasing blocking artifacts. The experimental results show that our method obtains an average detection accuracy of 98% on the UCID image database. Another advantage of our proposed method is that it has only one-dimensional feature and time-saving. Furthermore, we use the game theory to evaluate the performance of both sides, and identify the optimal strategies of both sides.