An Efficient Three-Phase Fuzzy Logic Clone Node Detection Model

Abstract

Wireless sensor networks have been deployed in the open and unattended environment where the attacker can capture the sensors and create the replica of captured nodes. As the clone nodes have been considered legitimate nodes, clone nodes can initiate different network attacks. We have designed a three-phase clone node detection method named fuzzy logic clone node detection (FLCND). The first phase of FLCND checks whether any node is missing from the network or not. In the next phase, FLCND finds out whether any missing node has arisen in the network in a stipulated time. If any missing node is alive, there is a possibility the node may be cloned. The information of suspected nodes is entered into the Hot-List, which has been maintained in the network. Phase III uses the suspected list and finds out the possibility of clone node using fuzzy logic. Two different scenarios have been simulated in NS2 to evaluate FLCND. The simulation result shows that the proposed method increases the packet delivery ratio (PDR) and reduces packet loss, end-to-end delay, and energy consumption. The simulation results illustrate that the FLCND method reduces the average power consumption by 27% and increases the detection rate by 46% compared to the existing techniques.