HEED: A Hybrid, Energy-Efficient, Distributed Clustering Approach for Ad Hoc Sensor Networks
IEEE Transactions on Mobile Computing
A dynamic en-route scheme for filtering false data injection in wireless sensor networks
Proceedings of the 3rd international conference on Embedded networked sensor systems
A probabilistic voting-based filtering scheme in wireless sensor networks
Proceedings of the 2006 international conference on Wireless communications and mobile computing
A survey on clustering algorithms for wireless sensor networks
Computer Communications
A weight-based clustering multicast routing protocol for mobile ad hoc networks
International Journal of Internet Protocol Technology
Fuzzy key dissemination limiting method for the dynamic filtering-based sensor networks
ICIC'07 Proceedings of the intelligent computing 3rd international conference on Advanced intelligent computing theories and applications
Key inheritance-based false data filtering scheme in wireless sensor networks
ICDCIT'06 Proceedings of the Third international conference on Distributed Computing and Internet Technology
Routing techniques in wireless sensor networks: a survey
IEEE Wireless Communications
IEEE Communications Magazine
Statistical en-route filtering of injected false data in sensor networks
IEEE Journal on Selected Areas in Communications
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Sensor networks are the next generation of technology for use in various applications, including tracking, monitoring and control. However, sensor networks still have some inherent security and hardware problems. The cluster routing scheme has been proposed in attempt to reduce duplication reports. Moreover, statistical en-route filtering (SEF) has been proposed to detect and drop the injected fabricated report found in the sensor network. When SEF method is applied in cluster-based sensor networks, their detection capabilities may be quite poor because the proposed schemes do not consider each possible feature that may be present. To solve this problem, we propose a cluster adaptation method to enhance the performance of SEF. The proposed method uses a fuzzy logic approach to form an efficient cluster for SEF. The sufficient performance of the proposed method is shown by the simulation results.