Abstract Recently, image encryption is becoming increasingly important, many chaotic models have been prevalently used to design kinds of cryptographic schemes in chaos cryptography. Among those models, coupled map lattice (CML), as a classics spatiotemporal chaotic model with good performance, is popularly used for those chaos-based cryptographic schemes. However, there exist no scientific studies in the three dimensional (3D) CML model from the view of theoretical and application perspectives besides our previous research. To further improve the complicated chaotic dynamic behavior and extend the application scenarios of CML into a3D CML one, therefore it is introduced into our paper for constructing chaos-based image encryption scheme with higher security. First of all, properties of 3D CML are comprehensively analyzed to fully verify that it possesses more complicated chaotic behavior than one dimensional and two dimensional CML. Subsequently, the chaotic sequences are produced by means of intercepting 32 bit from each node of the 3D CML model, both NIST and TestU01 testing certificate those chaotic sequences have high randomness, which are pretty suitable for designing the chaos-based cryptographic scheme. Based on those above-mentioned analyses, a new color image encryption scheme is proposed via diffusion and confusion. In our scheme, diffusion is performed based on those above-mentioned chaotic sequences via the 3D CML model, while confusion is carried out according to the Baker map. Specially, before diffusion and confusion operations, red, green and blue channel of a plain color image are combined into one pixel including 24 bit (0 or 1) for improving the efficiency of our scheme. To sum up, all corresponding simulations show our scheme has excellent encryption performance, and it would be popularly applied in the real-life cryptographic domains. Our research contributes to enriching the theoretical research on chaotic cryptography and provides new chaotic image encryption schemes.

Abstract Face recognition has been widely used in many fields and has become an important identification method. The templates in face recognition systems are associated with the facial biometric features of users, and once leaked, it will pose a persistent threat to the users. Therefore, it is particularly important to protect the security of templates. In this work, a novel face template protection scheme is proposed by combining chaotic map, error correction code and locality sensitive hashing. The scheme utilizes two sets of parameters: global keys and user keys, and the generated data consists of two parts: storage key and biometric template. When generating a template, the extracted feature vector is permuted by using chaotic sequences to disrupt the correlation between different dimensions. Then, the user keys are processed by error correction code to generate the storage key, which can be used to recover the user keys during authentication. Finally, the permuted vector is processed by the proposed random number based locality sensitive hashing to generate biometric template. Experimental results and theoretical analysis show that the scheme has good accuracy and security, and can effectively resist various attacks on the face template.