OPTIMIZED HYBRID ROUTING ALGORITHM WITH ENHANCED TRANSMISSION SPEED IN WIRELESS SENSOR NETWORKS FOR AMI APPLICATION UNDER INDIAN GOVERNMENT ACT 1933
DOI:
https://doi.org/10.52152/801449Keywords:
Cyber-attack, Data Transmission, Machine Learning, shortest path, Attack time, Hybrid algorithm.Abstract
In the present digital era, data transmission plays a crucial role across diverse technological platforms. Ensuring data availability during transmission is crucial, since Wireless Sensor Networks (WSNs) in the Advanced Metering Infrastructure (AMI) domain are highly susceptible to cyber-attacks. These threats often result in inefficient routing and data breaches, raising serious security concerns. To address these challenges, this article introduces a shortest-path hybrid model that improves both the speed and security of data transmission by integrating Lion Optimization, Ant Colony Optimization (ACO), and Particle Swarm Optimization (PSO). The longer a data packet remains in transit, the higher the likelihood of it being intercepted, altered, or discarded by an attacker. Routing strategies that identify the shortest or least congested routes help lower latency, thereby decreasing the risk of blackhole, selective forwarding, and eavesdropping attacks. Similarly, algorithms that enable rapid path recovery and maintain fast transmission ensure resilience against denial-of-service (DoS) and routing loop attacks. The proposed model, Particle Bee Ant Colony Swarm (PBACS), improves transmission efficiency by identifying the optimal path between nodes, thereby reducing delay and outperforming conventional techniques. Enhancing data transmission speed explicitly diminish the attack time period for attackers and acts as impediment to cyber attacks along the transmission path and the effectiveness of this method is evaluated using five key performance metrics: throughput, packet loss, energy consumption, and delay.
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