Steganography forensics method for detecting least significant bit replacement attack

Abstract

Abstract. We present an image forensics method to detect least significant bit replacement steganographyattack. The proposed method provides fine-grained forensics features by using the hierarchical structurethat combines pixels correlation and bit-planes correlation. This is achieved via bit-plane decomposition anddifference matrices between the least significant bit-plane and each one of the others. Generated forensics fea-tures provide the susceptibility (changeability) that will be drastically altered when the cover image is embeddedwithdatatoformastegoimage.Wedevelopedastatisticalmodelbasedontheforensicsfeaturesandusedleastsquare support vector machine as a classifier to distinguish stego images from cover images. Experimentalresults show that the proposed method provides the following advantages. (1) The detection rate is noticeablyhigher than that of some existing methods. (2) It has the expected stability. (3) It is robust for content-preservingmanipulations, such as JPEG compression, adding noise, filtering, etc. (4) The proposed method providessatisfactory generalization capability.