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Adaptive security design with malicious node detection in cluster-based sensor networks
Affiliation:1. Department of Computer Science and Engineering, Sungkyunkwan University, Republic of Korea;2. Department of Interaction Science, Sungkyunkwan University, Republic of Korea;3. Department of Computer Science and Engineering, University of Minnesota, USA
Abstract:Distributed wireless sensor networks have problems on detecting and preventing malicious nodes, which always bring destructive threats and compromise multiple sensor nodes. Therefore, sensor networks need to support an authentication service for sensor identity and message transmission. Furthermore, intrusion detection and prevention schemes are always integrated in sensor security appliances so that they can enhance network security by discovering malicious or compromised nodes. This study provides adaptive security modules to improve secure communication of cluster-based sensor networks. A dynamic authentication scheme in the proposed primary security module enables existing nodes to authenticate new incoming nodes, triggering the establishment of secure links and broadcast authentication between neighboring nodes. This primary security design prevents intrusion from external malicious nodes using the authentication scheme. For advanced security design, the proposed intrusion detection module can exclude internal compromised nodes, which contains alarm return, trust evaluation, and black/white lists schemes. This study adopts the two above mentioned modules to achieve secure communication in cluster-based sensor networks when the network lifetime is divided into multiple cluster rounds. Finally, the security analysis results indicate that the proposed design can prevent and detect malicious nodes with a high probability of success by cluster-based and neighbor monitor mechanisms. According to the performance evaluation results, the proposed security modules cause low storage, computation, and communication overhead to sensor nodes.
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