Abstract
In the event-driven wireless sensor networks (EWSNs), the event of interests occurs irregularly and at random in the network. Then, sensor nodes near the event sense the event and send out data packets of the event. Next, router nodes (RNs) forward those packets to the sink node (SN) by multi-hop communications. Compromised RNs would become malicious and launch selective forwarding attacks by dropping part of or all the packets from other nodes. On the other hand, a harsh environment makes the channel poor, so the routing nodes under a harsh environment have low packet forwarding rates because they sometimes have to give up forwarding the current packets after many tries to forward them due to poor channel. If the malicious nodes' forwarding rates become close to those of nodes under a harsh environment, the schemes based on packet forwarding rates for detecting selective forwarding attack may fail because they cannot differentiate the low data packet forwarding rates resulting from the malicious behaviors or harsh environment. To solve this problem, we provide a combined scheme for detecting selective forwarding attack in wireless sensor networks (WSNs) under harsh environments. This scheme employs a data clustering algorithm (DCA) to screen the malicious nodes out by clustering their cumulative forwarding rates (CFRs) and designs a voting decision method to protect the nodes under a harsh environment from being judged as malicious nodes. The simulation results show that our scheme has a low false detection rate (FDR) of 1% and a low missed detection rate (MDR) of 5% respectively with negligible energy consumption in WSNs under a local variable harsh environment.
Highlights
A 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
Generalize data clustering algorithm to adapt it to Event-driven wireless sensor networks (EWSNs) which are different from clustered WSN in our previous schemes
The combination of data clustering algorithm and neighbor voting decision method makes the detection against selective forwarding attacks more effective in missed detection rate (MDR), false detection rate (FDR), and network throughput
Summary
A 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. VOLUME 9, 2021 the malicious nodes from normal nodes according to the nodes’ reputation based on the nodes’ forwarding behaviors In these schemes, the threshold values depend on the estimation of their channel quality. The DCA-based schemes proposed in our previous work [46]–[48] cluster the nodes’ behaviors to distinguish the malicious nodes from normal nodes. These schemes assume the network work in a normal environment with good channel quality. In the harsh environment, the poor channel may reduce the current forwarding rates and CFRs severely, a normal node with a lower CFR may be misjudged as a malicious node in these schemes.
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