Steganalysis of Adaptive JPEG Steganography by Selecting DCT Coefficients According to Embedding Distortion

2015 KSII Transactions on Internet and Information Systems  
According to the characteristics of adaptive JPEG steganography which determines the changed DCT coefficients based on embedding distortion, a new steganalysis method by selecting the DCT coefficients with small distortion values is proposed. Firstly, the principle of adaptive JPEG steganography through minimizing distortion is introduced. Secondly, the practicability of selecting the changed DCT coefficients according to distortion values is studied. Thirdly, the proposed steganalysis method
more » ... given and the embedding sensitivity of the steganalysis feature extracted from the selected DCT coefficients is analyzed. Lastly, the implement processes of the proposed method are presented and analyzed in details. In the experiments, PQt, PQe and J-UNIWARD steganography are used as examples to verify the effect of the proposed steganalysis method for adaptive JPEG steganography. A serial experimental results show the detection accuracy can be improved obviously, especially when the payload is relatively low. Image Steganography is the science and art of convert communication which try to embed the secret messages into innocuous-looking cover image [1] . The countermeasure against steganography technology is steganalysis [2] which focuses on detecting the presence of the secret messages. In recent years, with the development of Internet and steganography technologies, more and more algorithms and softwares are constantly emerging and can be got easily. It enables people to exchange their information conveniently. However, this also provides fertile grounds for illegal parties to disseminate their messages to each other secretly by utilizing steganography technologies. Therefore, image steganalysis which try to develop techniques for detecting this secret messages exchange is becoming more and more important. JPEG is one of the most popular image formats on the internet, thus the steganography and steganalysis technology about JPEG image attract more attentions. For now, the steganography algorithms for JPEG image can be divided into non-adaptive steganography and adaptive steganography. The former includes Jsteg [3], MB1 [4], MB2 [5], Outguess [6], F5 [7], PQ (Perturbed Quantization) [8], MME (Modified Matrix Encoding) [9], nsF5 [10], etc. The latter includes PQt (texture-adaptive PQ), PQe (energy-adaptive PQ) [10], MOD (Model Optimized Distortion) [11], NPQ (Normalized Perturbed Quantization) [12], EBS (Entropy Block Steganography) [13], UED (Uniform Embedding Distortion) [14], J-UNIWARD (JPEG UNIversal WAvelet Relative Distortion) [15], SI-UNIWARD (Side-informed UNIWARD) [15] and so on. Moreover, in literature [16] , a new framework for designing distortion functions of JPEG image is proposed by dividing the DCT coefficients into first-priority-group and first-priority-group. The adaptive JPEG steganography constrains the embedding changes to the textured or perceptual complex image regions, and then a higher level of stego-security can be achieved since the embedding noise is covered by the inhered noise. For the above adaptive JPEG steganography algorithms, the steganographic schemes are similar. They all define a distortion function which is related with statistical undetectability firstly and then the messages are embedded by encoding method. For example, as to PQt and PQe, the distortion function is defined according to the texture and energy measure of 8×8 DCT block respectively, and then the given messages are embedded by wet paper code [17]; as to MOD, NPQ, EBS, UED, J-UNIWARD and SI-UNIWARD, the different distortion functions are defined respectively and the messages are embedded while minimizing the distortion function by STCs (Syndrome-Trellis Codes) [18] . For the typical non-adaptive JPEG steganography algorithms, many steganalysis methods have been proposed and achieved high detection accuracies [2] . As to the adaptive JPEG steganographic schemes, different steganalysis methods also have been investigated. In literature [19] , the authors pointed out that the distortion function of MOD steganography has been overtrained to an incomplete cover model. Then, a targeted steganalysis method for MOD is proposed by utilizing the statistical features beyond the optimized model. For other adaptive JPEG steganography, the steganographic security is often evaluated by blind steganalysis. For example, in literature [10], the 274-dimensional feature vector consisting of 193 extended DCT features and 81Markov features proposed in [20] is used to detect PQt and PQe. The detection accuracy can only reach to 72% when payload is 0.1bpac (bits per non-zero AC DCT coefficient); in literature [14] , the state-of-the-art CC-JRM (Cartesian Calibration JPEG Rich Model) [21] feature is employed to evaluate the security performances of UED steganography and the detection accuracy is about 60% when payload is 0.1bpac and QF (Quality Factor) is 75; in literature [15] , the CC-JRM and SRM (Spatial Rich Model) [22]
doi:10.3837/tiis.2015.12.026 fatcat:frnlay7mxff7pguiejqz54q2u4