Grayscale Image Authentication using Neural Hashing

Many different approaches for neural network based hash functions have been proposed. Statistical analysis must correlate security of them. This paper proposes novel neural hashing approach for gray scale image authentication. The suggested system is rapid, robust, useful and secure. Proposed hash function generates hash values using neural network one-way property and non-linear techniques. As a result security and performance analysis are performed and satisfying results are achieved. These features are dominant reasons for preferring against traditional ones.Comment: international journal of Natural and Engineering Sciences (NESciences.com) : Image Authentication, Cryptology, Hash Function, Statistical and Security Analysi

An Adaptive Image Encryption Scheme Guided by Fuzzy Models

A new image encryption scheme using the advanced encryption standard (AES), a chaotic map, a genetic operator, and a fuzzy inference system is proposed in this paper. In this work, plain images were used as input, and the required security level was achieved. Security criteria were computed after running a proposed encryption process. Then an adaptive fuzzy system decided whether to repeat the encryption process, terminate it, or run the next stage based on the achieved results and user demand. The SHA-512 hash function was employed to increase key sensitivity. Security analysis was conducted to evaluate the security of the proposed scheme, which showed it had high security and all the criteria necessary for a good and efficient encryption algorithm were met. Simulation results and the comparison of similar works showed the proposed encryptor had a pseudo-noise output and was strongly dependent upon the changing key and plain image.Comment: Iranian Journal of Fuzzy Systems (2023

Building Secure and Fast Cryptographic Hash Functions Using Programmable Cellular Automata

Cryptographic hash functions have recently brought an exceptional research interest. With the increasing number of attacks against the widely used functions as MD5, SHA-1 and RIPEMD, the need to consider new hash functions design and conception strategies becomes crucial. In this paper, we propose a fast and efficient hash function using programmable cellular automata that are very suitable for cryptographic applications due to their chaotic and complex behavior derived from simple rules interaction. The proposed function is evaluated using several statistical tests, while obtained results demonstrate very admissible cryptographic properties such as confusion/diffusion capability and high sensitivity to input changes. Furthermore, the hashing scheme can be easily implemented through software or hardware, so it provides very competitive running performances