A Compressive Sensing Based Image Encryption and Compression Algorithm With Identity Authentication and Blind Signcryption

Recently, a robust and secure image sharing scheme with personal identity information embedded was proposed based on Compressive Sensing, Secret Image Sharing and Diffie-Hellman Agreement. However, there exists a security flaw in this scheme. It cannot resist the man-in-the-middle attack in the authentication stage. Anyone can disguise himself as a legal person and get the information when exchanging the secret keys, which provides the possibility for information leakage, tampering, and other attacks. In this paper, we propose an image encryption and compression algorithm with identity authentication and blind signcryption based on Parallel Compressive Sensing (PCS), Secret Sharing(SS) and Elliptic Curve Cryptography (ECC). Firstly, Logistic-Tent system and PCS are employed to complete compression and lightweight encryption in the compression stage. Secondly, random sequences are generated based on Chebyshev map to construct four encryption matrices to perform the encryption process. Meanwhile, the participants' identity authentication and blind signcryption can be achieved by using ECC. Finally, we prove the efficiency and security of the blind signcryption, which can authenticate the participants' identity before restoring the original image. Experiments and security analysis demonstrate that the proposed scheme not only reduce the storage space and computational complexity effectively, but also has resistance against the man-in-the-middle attack, forgery attack and chosen-text attack.