A novel approach for secure compressive sensing of images using multiple chaotic maps

In this paper, a novel approach for secure compressive sensing of images based on multiple one dimensional chaotic maps is proposed. The basic idea is to perform the random selection of a combination of two one dimensional chaotic maps to generate a random stream. One or more values from the random stream are used to generate each normal value in the random measurement matrix for compressive sensing. In the proposed approach, eight different one dimensional chaotic maps are used. For one measurement matrix generation, two of them are randomly selected based on a secret key. The number of iterations and the initial states of the chaotic maps are also decided by external secret keys. The chaotic output of iterations of the two selected chaotic maps are XORed to generate a new chaotic value so that the measurement matrix so generated can withstand known plaintext attack. The block-based compressive sensing (BCS) of images is adopted to validate the proposed system. Further enhancement in the security of the proposed system for BCS of images can be obtained by using different measurement matrices for different blocks of images. An algorithm for generating multiple measurement matrices is also presented in this work. It is experimentally proved that the proposed encryption system can maintain the robustness to noise of the compressive sensing system. The proposed robust encryption system is subjected to several forms of attacks and is proved to be resistant against all.

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