Open AccessSVD‐based image compression, encryption, and identity authentication algorithm on cloud
Author(s) -
Yu Changzhi,
Li Hengjian,
Wang Xiyu
Publication year - 2019
Publication title -
iet image processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.401
H-Index - 45
eISSN - 1751-9667
pISSN - 1751-9659
DOI - 10.1049/iet-ipr.2018.5912
Subject(s) - singular value decomposition , encryption , algorithm , singular value , authentication (law) , ciphertext , computer science , matrix (chemical analysis) , image (mathematics) , mathematics , theoretical computer science , computer vision , computer security , eigenvalues and eigenvectors , physics , materials science , composite material , quantum mechanics
Based on singular value decomposition (SVD), an image compression, encryption, and identity authentication scheme is proposed here. This scheme can not only encrypt image data which would store in the cloud but also implement identity authentication. The authors use the SVD to decompose the image data into three parts: the left singular value matrix, the right singular value matrix, and the singular value matrix. The left singular value matrix and right singular value matrix are not as important as the singular value matrix. They propose a logistic‐tent‐sine chaotic system to encrypt them. In this scheme, they proposed a novel authentication value calculation algorithm, which can calculate the authentication value according to related data. According to the authentication value calculated from the ciphertext, the algorithm has the perfect authentication performance, so as in the scenarios if the image is cropped or added noisy. Theoretical analysis and empirical evaluations show that the proposed system can achieve better compression performance, satisfactory security performance, and low computational complexity.