Identity Based Attack Detection using Spatial Information in Clusters for Wireless Sensor Network - Das, Tuhin; Sachin D, Choudhari (International Journal of Computer Sciences and Engineering, 2025)
Wireless Sensor Network is a network of wireless devices which is spatially distributed in autonomous tiny computing devices and equipped with sensors, a wireless radio, a processor, and a power source. Wireless sensor networks are deployed in the physical environment to monitor and gather a wide range of information. Due to its dynamic operational and manhandled mobile devices used it also suffers from lot of network security threats. Mostly identity based attacks for example masquerade uses MAC address of some authorized person through malicious device to get hold of the secret information inside the wireless network which largely affects the performance of the network. Identifying a device appropriately is a massive challenge in network securities domain which can be perfectly executed by using the spatial information, a physical property of wireless sensor node. We propose OADL (Optimized Attack Detection & Localization) model which uses the average received signal gain of received signal strength with spatial information correlation to find out the identity of attacker and again using PAM clustering algorithm for detecting the number of with multiple illegitimate identities and eliminate them. When we have the datasets discovered by support vector machines can be used to localize the exact position of multiple illegitimate identities. Evaluating this technique using both wifi (802.11 network) and zigbee model (802.15.4 network) we are able to determine result that attained more than 90% percent hit rate. Using integrated detection and localization algorithms provide high accuracy for multiple attackers.