Enhancing Data Access Security through the Utilization of [2048,512,4] Linear Code

Linear code is a type of error-correcting code that satisfies the property of closure under addition. Linear codes have been a major component in data security and cryptography and has been proven as an important tool in maintaining privacy. Linear code, [n,k,d] is a type of linear code with specific parameters that describe its properties and capabilities with n being the length of codewords, k, the dimension of the code and d denotes the minimum Hamming distance. Code [2048,512,4] is an example of [n,k,d] Linear code with large codeword length, high dimension and a moderate minimum hamming distance. It was generated by a combination of two of [1024,256,4] linear code and its validity has been verified and confirmed using Gilbert Varshamov bound. This paper proposes a technique to enhance data access security by utilizing linear code [2048,512,4]. The proposed algorithm utilizes a sophisticated linear code equivalence test methodology to create a robust and secure system that generates and validates unique [2048, 512, 4] linear codes. These codes serve as highly effective authentication mechanisms, granting individualized access privileges to different users within the system. Also, by employing cutting-edge techniques in linear code equivalence testing, the algorithm ensures the generation of distinct and non-repeating [2048, 512, 4] linear codes, uniquely tailored to be each user's credentials. The analysis of the results reveals that to breach such a security measure, an intruder would need to contend with a vast number of permutations and combinations. In particular, there are 2048 P 2048 patterns and an astounding 131,328 distinct combinations of codewords that remain unknown to any potential breacher. These findings underscore the robustness and invulnerability of the proposed technique for enhancing data access security. The proposed technique also demonstrates a potential for significantly enhancing the protection of sensitive data for organisations in both pre-quantum and post quantum computing within the digital ecosystem.