Active steganalysis based on adapted Lempel-Ziv complexity and approximate entropy estimation

Steganalysis is the aptitude of identifying stegogrammes that contain a secret message. To test the steganalysis algorithm touching the unusual Stego images to ensure its robustness. This paper proposes an active steganalysis method uses irregularity in the stego image or the specialized algorithm is used to detect the existence of stego image. DCT coefficients are intended for each block. Approximate entropy estimation is used to normalize the randomness in a time series. Lempel-Ziv complexity characterizes the degree of order or disorder and development of spatiotemporal patterns. Moreover, adapted Lempel-Ziv complexity added to decide the block size. Second order statistics estimates the codebook, document to store the message. The proposed steganalysis deduces the properties of the hidden message in high rate embedding stego image. The evaluation scheme has a better performance of evaluating the steganalysis algorithm and can provide a quantitative evaluation criterion for steganalysis algorithm.