Intrusion Detection Using Rule Based Approach in RPL Networks

Day by day applications of wireless sensor networks is increasing in areas like environmental monitoring, agriculture, defence, Internet of Things. These networks use IPv6 based protocol namely Routing Protocol for Low power and Lossy networks(RPL). The sensor nodes have limited resources. They carry sensitive information and are placed in the hard to reach areas. Intrusion Detection System (IDS) plays an important role in providing the security for such systems. An IDS model is designed using Artificial Neural Networks, Logistic Regression, Support Vector Machine, and Random Forest techniques are analyzed on simulated data, WSN-DS, and IEEE-IoT-IDS to identify the suitable model for rule generation. Later, multiple attacks are identified using Rule Based Approach. The rule generation is carried out at the base station in order to utilize the sensor node’s energy efficiently. Experimental results show that the proposed method gives good results in the identification of multiple intrusions.