Enhancement of Network Security in MANET Using Refined Adaptive Harris Hawks Optimization Algorithm (RAHHO) for IoT Applications

The proliferation of Internet of Things (IoT) devices in Mobile Ad-Hoc Networks (MANETs) has introduced complex security challenges, demanding innovative solutions to safeguard data integrity and network functionality. This paper proposes a novel approach, the Refined Adaptive Harris Hawks Optimization Algorithm (RAHHO), tailored to fortify network security within MANETs for IoT applications. The RAHHO method integrates the efficient search capabilities of the Harris Hawks Optimization (HHO) algorithm with a dynamic updating mechanism, enhancing convergence speed and accuracy in optimizing security parameters. Leveraging the adaptability of HHO, RAHHO dynamically adjusts hawk positions and updates search strategies, enabling robust exploration of security parameter spaces crucial for MANETs. Moreover, the application of RAHHO in MANETs offers a multifaceted enhancement of security measures. The outcomes reveal varying degrees of susceptibility to attacks, with HHO displaying the highest vulnerability, followed by CHHSO and MU-HHO. RAHHO emerges as notably more resilient, being 73.33% less vulnerable than HHO, 40.5% less vulnerable than CHHSO, and 20% less vulnerable than MU-HHO. Simulation results demonstrate the efficacy of RAHHO in reinforcing network security, showcasing notable improvements in network performance metric such as cost function. The results establish RAHHO as the most secure algorithm in this specific context, showcasing superior performance. The progressive decrease in vulnerability from HHO to RAHHO corresponds to an increase in overall security.