The security of RC4 algorithm using keys generation depending on user's retina

Abstract

Digital technologies grow more rapidly; information security threats are becoming increasingly dangerous. Advanced and various cyber-attacks and security threats, like targeted emails, and information exploitation, pose a critical threat that basically undermines our trust in the digital society. Rivest cipher 4 (RC4) algorithm is a significant cipher of a stream that could be utilized with protocols of the internet, the advantage of the RC4 algorithm is that it is simple and effective. There are several weak, especially after the pseudo-random generation algorithm (PRGA), PRGA's initially 256 rounds (the amount of the RC4 permutation). Several modified RC4 studies have been published thus far, however, they all face either standard privacy or achievement evaluation issues. This paper proposes a new RC4 algorithm that is based on the user's retina (RC4-Retina), which has solved both of these weak points it was indicated in the standard RC4 algorithm. The novelty of retina key scheduling algorithm (RKSA), which is generated by relying on the user's retina of the algorithm will modify the matrix of permutation used to configure the keys. The efficiency of the improved algorithm was measured by depending on the average security of ciphertext of different keys and different messages, results were good compared to the standard algorithm.

Enhanced ARIA-based counter mode deterministic random bit generator random number generator implemented in verilog

“…The CTR-DRBG algorithm, widely used for secure random number generation, faces several inherent issues [38]- [40]. Firstly, in the derivation function, generating secure random numbers using the counter value leads to increased computational time as the counter starts at 0 and increments, causing a significant rise in computation time with larger counter values [41]. Particularly, the necessity to reset upon each counter value change consumes time during operations.…”

Using Crossover Area of the Retinal Eye to Generate a Secret Key Based on Deep Learning- YOLO-v5 Object Detection Algorithm

“…Mazher and Waleed [16] Retina features extracted using glowworm swarm optimization algorithm Chaotic map used for high-quality random cryptographic key generation GSO algorithm extracts retina features for random key generation. Salih and Mahdawi [17] Proposed RC4-Retina algorithm based on user's retina. Introduced retina key scheduling algorithm (RKSA) for key generation.…”

“…Retinal biometric features offer high precision due to their stability over a lifetime [20]. Previous work, such as Tajuddin and Nandini [15], Mazher and Waleed [16], Salih and Mahdawi [17], Alrifaee and Ismaeel [18], has demonstrated the use of retinal biometric data for cryptographic key generation and key management, leveraging the uniqueness and stability of the retinal blood vessel patterns. The proposed algorithms and techniques aim to enhance the security and reliability of cryptographic systems by utilizing the retinal biometric modality.…”