A Learning-Based Steganalytic Method against LSB Matching Steganography

This paper considers the detection of spatial domain least significant bit (LSB) matching steganography in gray images. Natural images hold some inherent properties, such as histogram, dependence between neighboring pixels, and dependence among pixels that are not adjacent to each other. These properties are likely to be disturbed by LSB matching. Firstly, histogram will become smoother after LSB matching. Secondly, the two kinds of dependence will be weakened by the message embedding. Accordingly, three features, which are respectively based on image histogram, neighborhood degree histogram and run-length histogram, are extracted at first. Then, support vector machine is utilized to learn and discriminate the difference of features between cover and stego images. Experimental results prove that the proposed method possesses reliable detection ability and outperforms the two previous state-of-the-art methods. Further more, the conclusions are drawn by analyzing the individual performance of three features and their fused feature

Steganalytic Methods for the Detection of Histogram Shifting Data Hiding Schemes

Peer-reviewedIn this paper, several steganalytic techniques designed to detect the existence of hidden messages using histogram shifting schemes are presented. Firstly, three techniques to identify specific histogram shifting data hiding schemes, based on detectable visible alterations on the histogram or abnormal statistical distributions, are suggested. Afterwards, a general technique capable of detecting all the analyzed histogram shifting data hiding methods is suggested. This technique is based on the effect of histogram shifting methods on the ¿volatility¿ of the histogram of the difference image. The different behavior of volatility whenever new data are hidden makes it possible to identify stego and cover images

El uso de bloques de imagen en el dominio espacial como una vía robusta de estenografía

Steganography is a way to convey secret communication, with rapid electronic communication and high demand of using the internet, steganography has become a wide field of research and discussion. In this paper a new approach for hiding information in cover image proposed in spatial domain, the proposed approach divides the host image into blocks of size (8x8) pixels and message bits are embeds into the pixels of a cover image. The 64-pixel values of each block converted to be represented in binary system and compared with corresponding secret data bits for finding the matching and hold 6-pixels. The search process performed by comparing each secret data bit (8-bits) with created binary plane at the cover image, if matching is found the last row of the created binary plane which is (LSB) is modified to indicate the location of the matched bits sequence “which is the secret data” and number of the row, if matching is not found in all 7th rows the secret sequence is copied in to the corresponding 8th row location.The payload of this technique is 6 pixels’ message (48-bits) in each block. In the experiments secret messages are randomly embedded into different images. The quality of the stego-image from which the original text message is extracted is not affected at all. For validation of the presented mechanism, the capacity, the circuit complexity, and the measurement of distortion against steganalysis is evaluated using the peak-signal-to-noise ratio (PSNR) are analyzed