Towards Improved Steganalysis: When Cover Selection is Used in Steganography

Abstract

This paper proposes an improved steganalytic method when cover selection is used in steganography. We observed that the covers selected by existing cover selection methods normally have different characteristics from normal ones, and propose a steganalytic method to capture such differences. As a result, the detection accuracy of steganalysis is increased. In our method, we consider a number of images collected from one or more target (suspected but not known) users, and use an unsupervised learning algorithm such as k-means to adapt the performance of a pre-trained classifier towards the cover selection operation of the target user(s). The adaptation is done via pseudo-labels from the suspected images themselves, thus allowing the retrained classifier more aligned with the cover selection operation of the target user(s). We give experimental results to show that our method can indeed help increase the detection accuracy, especially when the percentage of stego images is between 0.3 and 0.7. INDEX TERMS Cover selection, steganography, steganalysis, clustering. communication engineering, in 2003, from Xi'an Jiaotong University, China. Since November 2017, he has been a Professor of cyber security with the University of Kent, U.K., leading the university wide Kent Interdisciplinary Research Centre in Cyber Security (KirCCS), a U.K. government recognized Academic Centre of Excellence in Cyber Security Research (ACE-CSR). He has published over 100 scientific articles with two Best Paper Awards. His research interests include cyber security, human-computer interface, multimedia computing, digital forensics, and cybercrime. XINPENG ZHANG (M'11) received the B.S. degree in computational mathematics from Jilin University, China, in 1995, and the M.E. and Ph.D. degrees in communication and information system from Shanghai University, China, in 2001 and 2004, respectively. Since 2004, he has been with the faculty of the School of Communication and Information Engineering, Shanghai University, where he is currently a Professor. His research interests include information hiding, image processing, and digital forensics. He has published over 200 articles in these areas.