EFFICIENT MALICIOUS NODE DETECTION IN WIRELESS SENSOR NETWORKS USING RABIN-KARP ALGORITHM

The resource-constrained nature of Wireless Sensor Networks (WSNs) makes efficient identification of rogue nodes a significant problem. A scalable, lightweight algorithm that can detect and mitigate harmful behavior is the goal of this effort to improve network security. The Rabin-Karp method, well-known for its pattern-matching efficiency, is modified to verify transmitted data packets using hashes. To guarantee the integrity of data flow inside the network, the technique uses hash comparisons to identify inconsistencies suggestive of rogue nodes. Maintaining high detection accuracy while reducing computing overhead, false positives, and energy consumption is the goal of the approach to be designed. To optimize network performance, the algorithm runs at the level of the cluster heads and filters packets before they reach the base station. The objective is to provide a dependable, scalable, and energy-efficient solution for WSN security. This will ensure that data remains intact and that rogue nodes cannot disrupt the network. This method improves the reliability of WSNs and guarantees continuous monitoring, making them ideal for mission-critical applications. Incorporating the Rabin-Karp algorithm solves the urgent problem of trustworthy malicious node identification in contemporary WSNs by striking a compromise between computational efficiency and effective security.