Hybrid Optimization to Trust Enhanced Secure Routing Optimization with IABC and CGWAA for MANET

Abstract

Routing in Mobile Ad Hoc Networks (MANET) presents significant challenges due to the dynamic nature of network topology. Optimal route selection and efficient route discovery are matched by effective routing in MANET. This study proposes a Hybrid Optimization to Trust-Enhanced Secure Routing Optimization (HO-TESRO) designed to address these challenges in IoT environments by integrating metrics such as link stability, bandwidth, energy, and trust. The HO-TESRO model employs the Improved Artificial Bee Colony (IABC) algorithm to select optimal routes and utilizes the Chaotic Grey Wolf Adaptive Algorithm (CGWAA) algorithm in combination with the Advanced Encryption Standard (AES) to ensure secure communication. The trust-based CGWAA algorithm evaluates and selects the most secure and efficient multiple paths, while the AES-CGWAA mechanism validates node keys and shared codes for each data transfer, ensuring a safe connection. The proposed model was evaluated using extensive simulations in MATLAB, and its performance was compared against existing techniques. The findings show major improvements in detection rate, throughput, packet loss ratio, latency, and packet delivery ratio. These findings underscore the efficacy of HO-TESRO in providing a robust, secure, and energy-efficient routing solution for IoT-based MANET, addressing critical issues of resource allocation and secure routing.