Enhancing Transmission Efficiency and Data Encryption Evaluation Using Fuzzy Logic: A Comprehensive Review and Novel Approach

Resumen

Fuzzy logic, inspired by human reasoning and intuition, extends traditional Boolean logic by incorporating degrees of truth between" completely true" and "completely false." It enables handling vague or imprecise concepts, such as "large" or "small," using partialtruths to arrive at conclusions. Versatile in nature, fuzzy logic can be implemented in hardware, software, or a combination of both, making it suitabl for applications ranging from small-scale devices to large industrial systems. It has been widely adopted in industries like automotive manufacturing, where it enhances quality, reduces development time, and lowers costs. Originally developed for data classification and handling, fuzzy logic has become a preferred approach for various control systems. In wireless sensor networks (WSNs), for example, fuzzy logic is utilized to optimize node clustering and xtend network lifetime. By selecting cluster heads through fuzzy logic, systems achieve improved efficiency, reduced energy consumption, and enhanced performance. Compared to existing methods, this approach offers superior results in metrics like First Node Dead (FND) and overall network functionality. Fuzzy logic also contributes to data security in network transmission. A novel method integrates fuzzy set theory with cryptography to enhance text data protection. Using the AES Rijndael algorithm, text is encrypted with a key and transformed into numeric values through fuzzy logic, with values ranging between 0 and 1. Decryption requires the original key, ensuring secure data retrieval. To bolster security further, a matrix transformation employing fuzzy membership functions is applied.