An Integrated Intrusion Detection Model of Cluster-Based Wireless Sensor Network

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, cluster-head 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.

• Publication year

  2015

• Venue

  PLoS ONE

• Publication date

  2015-10-08

• Fields of study

  Medicine, Computer Science, Engineering

• Identifiers
  DOI 10.1371/journal.pone.0139513PMID 26447696PMCID 4598086
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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