A Novel Hybrid Intrusion Detection Using Flow-Based Anomaly Detection and Cross-Layer Features in Wireless Sensor Network

Abstract

The emerging technology of Wireless sensor network is expected to provide Intrusion detection technique for all kind of attacks. This article models and analyzes intrusion detection using flow-based IDS and cross-layered approach. The Critical application needs to replace cryptographic technique with flow-based anomaly detection for secure communication and single layer detection method with multi-layer detection method for efficient attack detection. The proposed detection system has a two-phase approach. In the first phase, flow-based anomaly detection method is used to detect potential anomalies in the network traffic. During second phase cross–layer features are correlated to narrow down the possible attacks. Simulation results clearly show that the proposed detection technique has an excellent performance in terms of detection accuracy, the energy consumption, and the false positive rate will reduce than the layer-based approach and packet-based approach.