Master'sOpen Access

Compressive sensing and image encryption

2019
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Advisor: Doç. Dr. Sema Koç Kayhan

Abstract (EN)

Out of various cryptographic attacks, Chosen-Plaintext Attack (CPA) is one of the most powerful and widely used attack on encrypted images. In order to efficiently resist such a strong attack, a novel chaos and Compressive Sensing (CS) based image encryption algorithm is presented in this work. Firstly, the original plaintext image is compressed via Orthogonal Matching Pursuit with Partially Known Support (OMP-PKS) and then the compressed image is confused and diffused using TD-ERCS and Skew-tent chaotic maps, respectively. Correlation among the compressed pixels is break down via confusing the image pixels using TD-ERCS chaotic map. Skew-tent chaotic map is employed for the pixel diffusion process. To get the final ciphertext image, the confused pixels are further changed through bitwise XORed operation via random matrix. For the sake of higher security, the initial conditions of chaotic maps are made dependent on the plaintext image and the parameters are computed via SHA-512. Furthermore, to decrease the transmission bandwidth, the measurement matrix is generated via Beta chaotic map. Instead of sending the whole measurement matrix, the sender will just send the Beta chaotic map initial conditions and control parameters (key) values along with the compressed ciphertext. The reliability and robustness of the designed image compression and encryption scheme are verified via experimental analysis and simulation results. All the experimental and simulation results are in favour of the proposed scheme.

Author

Dr. Jan Sher Khan

How to Cite

Jan Sher Khan (Master Thesis). Compressive sensing and image encryption, 2019, Gaziantep University.

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