Abstract
Considering wireless sensor network characteristics, this paper combines anomaly and mis-use detection and proposes an integrated detection model of cluster-based wireless sensor network, aiming at enhancing detection rate and reducing false rate. Adaboost algorithm with hierarchical structures is used for anomaly detection of sensor nodes, clusterhead nodes and Sink nodes. Cultural-Algorithm and Artificial-Fish-Swarm-Algorithm optimized Back Propagation is applied to mis-use detection of Sink node. Plenty of simulation demonstrates that this integrated model has a strong performance of intrusion detection. Copyright:
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CITATION STYLE
Sun, X., Yan, B., Zhang, X., & Rong, C. (2015). An integrated intrusion detection model of cluster-based wireless sensor network. PLoS ONE, 10(10). https://doi.org/10.1371/journal.pone.0139513
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