SI-SLnO: Self-Optimized Secured Cross-Layer Networking IoT Networks Multi-Attack Detection Sea Lion Optimization
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Abstract
The trend of increased Internet of Things (IoT) devices in the critical infrastructure has aggravated security vulnerabilities in layers of network communication. Conventional security solutions implement MAC and routing layers separately, and they do not exploit cross-layer intelligence to achieve the best security and performance. In this paper, SI-SLnO is suggested to be a new Self-Improved Sea Lion Optimization algorithm combined with a secured cross-layer protocol, which optimizes both routing path choice and MAC-layer encryption using a dynamic risk evaluation. The protocol has a rule-based attack detecting mechanism which detects black hole attacks, selective forwarding attacks and wormhole attacks, with ElGamal cryptography being used to provide data privacy to adaptive MAC-layer. The broad simulations of SI-SLnO over different network sizes (250-1000 nodes) and attack density (25-100 infected devices) have shown that SI-SLnO has 13.78% lower routing cost, 25.58% less MAC overhead and 20% higher MAC protection frequency than the state-of-the-art optimization algorithms (GA, PSO, FF, CS, LA, CM-LA). Cross-layer architecture minimizes the security threats to 0.20658 whilst ensuring that the ratio of packet delivery exceeds 95 percent, thus it can be applied to IoT implementation in smart cities, industrial automation and healthcare monitoring systems with limited resources.
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