Detection and Prevention of Sinkhole Attack in Wireless Sensor Network using Armstrong 16-digit Key Identity and GAN Network

Abstract

Wireless Sensor Networks (WSNs) have collection of sensor nodes to collect information about the surrounding environment. WSN are used in many areas especially in health applications, industrial monitoring, military applications, environment monitoring applications etc. The sensor nodes have limited battery power and less memory and they are deployed in dangerous environments where they are not physically protected so they are subjected to different types of security attacks. One of the most common attacks is sinkhole attack where intruder capture or insert nodes in the sensor field that advertise routes to the base station. In this paper, a phenomenon is proposed against sinkhole attacks which detect malicious nodes which generate duplicate keys and cause power loss and packet drop. We are using AODV routing protocol to ensure secured transmission of data. Further, the system uses an ARMSTRONG 16-digit key to detect the malicious nodes which are trying to connect in the communication channel. GAN network is applied to dump the false nodes by identifying the fake ID data. Simulation results show that the proposed method successfully detects the sinkhole nodes for large sensor fields.