Enhancement of Network Security in MANETs using Modified Self-Optimization Algorithm (MSFO) for IoT Applications

The communication between smart devices in the Industrial Internet of Things relies heavily on Mobile Ad-hoc Networks (MANETs), allowing decentralized connectivity between nodes. Because of its digital qualities, encrypting one-dimensional data directly might be challenging. For this reason, a lightweight key frame extraction method is developed that is both safe and efficient for enhancing personal data confidentiality. Further, this proposed research aims to develop robust security protocol named Modified Sail Fish Optimization Algorithm (MSFO) for MANET-based IoT applications. The proposed approach introduce a chaotic cryptography-based privacy preservation model and optimizing the key generation process through a newly developed MSFO algorithm. The suggested MSFO model is tested for throughput and evaluated for effectiveness. Experimental observations and findings show that the suggested SA-SFO algorithm outperforms state-of-the-art algorithms. The PSO algorithm exhibited a decreasing trend in throughput, starting at 87.65% for 10 iterations and gradually declining to 77.23% by the 100th iteration. IASFO showed a similar trend but maintained higher throughput values compared to PSO, beginning at $\mathbf{9 2. 3 5 \%}$ and reducing to $\mathbf{8 4. 1 \%}$ over the same range. MSFO consistently outperformed both PSO and IASFO, with initial throughput of 95.4% at 10 iterations, which decreased to 88.1% at 100 iterations. These results demonstrate that MSFO provides superior performance in maintaining higher throughput values across the tested range.