A Data Clustering Algorithm for Detecting Selective Forwarding Attack in Cluster-Based Wireless Sensor Networks

Abstract

In cluster-based wireless sensor networks, cluster heads (CHs) gather and fuse data packets from sensor nodes; then, they forward fused packets to the sink node (SN). This helps wireless sensor networks balance energy effectively and efficiently to prolong their lifetime. However, cluster-based WSNs are vulnerable to selective forwarding attacks. Compromised CHs would become malicious and launch selective forwarding attacks in which they drop part of or all the packets from other nodes. In this paper, a data clustering algorithm (DCA) for detecting a selective forwarding attack (DCA-SF) is proposed. It can capture and isolate malicious CHs that have launched selective forwarding attacks by clustering their cumulative forwarding rates (CFRs). The DCA-SF algorithm has been strengthened by changing the DCA parameters (Eps, Minpts) adaptively. The simulation results show that the DCA-SF has a low missed detection rate of 1.04% and a false detection rate of 0.42% respectively with low energy consumption.Keywords: data clustering algorithm; selective forwarding attack; cumulative forwarding rate; cluster-based WSN IntroductionA wireless sensor network (WSN) is a self-organizing network formed by a mass of small and cheap sensor nodes, which have low energy, poor computing ability, and small storage. The cluster-based WSN has been widely applied in large-scale data gathering WSNs [1,2]. In the dense cluster-based WSN, as shown in Figure 1, member nodes (MNs) send data packets to their cluster heads (CHs). Then, CHs forward these packets to the next-hop CHs until they reach the sink node (SN). In this way, each CH does not have to exchange data with the SN directly. On the one hand, the direct communication between the CH and SN may fail due to the long-distance or poor channels. On the other hand, in some conditions, the energy cost of multi-hop communication is less than that of direct long-distance communication. All the nodes in the network take turns to act as CHs, so the energy consumption can get balanced. The network lifetime also becomes longer.

The DPC-Based Scheme for Detecting Selective Forwarding in Clustered Wireless Sensor Networks

“…The time complexity of ordinary DPC is O (n 2 ) [24]. n is the total number of points in the data set.…”

“…When DBSCAN is applied to detecting malicious nodes, these two parameters need to be determined according to the actual state of the clustered WSN, and they need to be adjusted according to the changes of the network. Fu et al [24] proposed a Dynamic Parameter-DBSCAN (DP-DBSCAN) scheme based on DBSCAN for resisting selective forwarding attack. In DP-DBSCAN, the parameters (Eps, MinPts) change depending on the network scenarios to offer better reliability in changing situations [25].…”

Combine Clustering With Game to Resist Selective Forwarding in Wireless Sensor Networks

“…H.Fu et al [19] proposed a selective forwarding attack detection scheme under the data clustering algorithm. The inspector nodes send the cumulative forwarding rate of the cluster heads to the sink node.…”

Two-Hop Monitoring Mechanism Based on Relaxed Flow Conservation Constraints against Selective Routing Attacks in Wireless Sensor Networks

“…Jamshidi et al [30] proposed a distributed lightweight method based on learning automata in order to select the most secure routes for forwarding packets, and thus avoiding those that contain malicious nodes. Fu et al [31] proposed data clustering algorithm to detect and isolate malicious cluster heads that launch selective routing attacks. Mehetre et al [32] introduced a trustable secure routing method for clustered WSNs that can also offer security through encryption and verification of packets on each source node.…”