A Novel Cryptographic Technique Using Amino Acid Compositions Enhanced by Artificial Intelligence Models

Encryption plays a vital role in securing sensitive digital data, and traditional cryptographic systems are usually not immune to high-level attackers. The current approaches often base on the use of traditional mathematical models that become more vulnerable to contemporary cyberattacks. The purpose of the current paper is to suggest a new cryptography method that would combine the properties of amino-acid based encoding with artificial intelligence to improve data security. The technique builds amino acid and binary encoding tables, and performs structured mappings along with using a secure key that is produced by permuting a cryptographically secure pseudorandom number generator. Randomized transformations and obfuscation steps are added to add more complexity. Experimental analysis has revealed that there were efficient encryption/decryption time with different file sizes and ciphertext distribution with randomness and key-sensitivity tests. The suggested approach offers an analogy of a bioinspiration-based and computationally resistant framework that can lead to future-generation cryptographic, which indicates the possible advantages of bioinformatics and AI in collaboration with cybersecurity.