This research proposes a novel approach for the efficient utilization of Intrusion Detection Systems (IDS) in Mobile Ad Hoc Networks (MANETs). The unique characteristics of MANETs, such as dynamic topology, limited resources, and lack of centralized control, pose challenges for traditional IDS deployments. The proposed approach leverages adaptive mechanisms and intelligent strategies to enhance the effectiveness and resource efficiency of intrusion detection in the dynamic and resource-constrained MANET environment.

The research introduces a context-aware IDS that dynamically adjusts its detection parameters based on the network’s changing conditions, including node mobility, traffic patterns, and communication behaviors. Additionally, the approach incorporates anomaly detection techniques and collaborative decision-making among nodes to improve detection accuracy and reduce false positives.

Simulation experiments are conducted using NS-3 (Network Simulator 3) to evaluate the performance of the proposed approach under various MANET scenarios. Key metrics, including detection accuracy, false positive rates, and resource utilization, are analyzed to assess the effectiveness of the adaptive and context-aware IDS.

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