Multiface Image Compression Encryption Scheme Combining Extraction With STP-CS for Face Database
Jun Mou, Linlin Tan, Yinghong Cao, Nanrun Zhou, Yushu Zhang
Abstract
With the rapid development of the Internet, face recognition technology is widely used, which makes the protection of face database especially important. To protect the recognized faces, a multiface image compression encryption (MFICE) scheme is designed based on the electromagnetic radiation Ktz neuron (ERKN). Since only faces are to be encrypted, they are first extracted. Then the face images are compressed by using semi-tensor product compressed sensing (STP-CS) algorithm, and the compressed images are integrated into a large cube, i.e., a 3-D cube. After that, interface confusion algorithm, 3-D shuffling algorithm, and 3-D diffusion algorithm are sequently performed by using chaotic sequences generated by iteration of ERKN, and finally the ciphertext image cube is obtained. The proposed scheme is evaluated, and it performs well in terms of feasibility and security.