A Game Theory-Based Intrusion Detection Model for Wireless Sensor Networks

An effective security practice for Wireless Sensor Networks (WSNs) needs to be formulated to address safety concerns. The operational life of a WSN depends on the amount of energy it consumes. It makes sense to employ a low-throughput Intrusion Detection System (IDS) to identify malicious intent. The existing IDSs are inadequate for detecting specific attacks and have a short operational lifespan due to high energy consumption. This article introduces an IDS that applies Game Theory (GT) and an autoregressive model to minimise power consumption and improve performance. The study advances the autoregressive paradigm to an uncooperative, complete-information, stationary GT that precisely predicts attack patterns. The alternative methodology empowers the methods that have been employed so far in two significant ways: (1) the utilisation of energy that is related to the procedure of identifying IDS, and (2) the optimality of the protection scheme, which balances the effectiveness of identification and the womanhood of power, is drawn by analysing the integrated remedy. The time required for the procedure is considered the primary measure of the method's energy production in the case study. According to the simulator results, the proposed IDS correctly predicts the timing of the assault and the targeting cluster to be used in the next step with the help of GT, while also reducing power consumption.

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