Intrusion Detection Based on State Context and Hierarchical Trust in Wireless Sensor Networks
Security problems have become obstacles in the practical application of wireless sensor networks (WSNs), and intrusion detection is the second line of defense. In this paper, an intrusion detection based on dynamic state context and hierarchical trust in WSNs is proposed, which is flexible and suitable for constantly changing WSNs characterized by changes in the perceptual environment, transitions of states of nodes, and variations in trust value. A multidimensional two-tier hierarchical trust mechanism in the level of sensor nodes (SNs) and cluster heads (CHs) considering interactive trust, honesty trust, and content trust is put forward, which combines direct evaluation and feedback-based evaluation in the fixed hop range. This means that the trust of SNs is evaluated by CHs, and the trust of CHs is evaluated by neighbor CHs and BS; in this way, the complexity of evaluation is reduced without evaluations by all other CHs in networks. Meanwhile, the intrusion detection mechanism based on a self-adaptive dynamic trust threshold is described, which improves the flexibility and applicability and is suitable for cluster-based WSNs. The experiment simulation and evaluation indicate that the mechanism we proposed outperforms the existing typical system in malicious detection and resource overhead.