E2V: Techniques for Detecting and Mitigating Rank Inconsistency Attack (RInA) in RPL based Internet of Things

Abstract

The Internet of Things (IoT) is a network of physical devices in which smart objects are interconnected that enable to collect and exchange the information via the internet. These devices are resource constrained and connected in the Low power and Lossy Networks (LLNs). Due to this nature, the RPL (IPv6 Routing Protocol for Low power and Lossy networks) is primarily designed for the resource constrained devices. But, this RPL undergoes various types of routing attacks. This paper considered the Rank Inconsistency Attack (RInA), which is illegitimately change the rank value and makes the network vulnerable. The proposed architecture E2V has three phases such as rank calculation, substantiation and malicious node elimination. The ultimate aim of E2V method is to detect and mitigate the RInA attack which includes sinkhole, selective forwarding and blackhole attacks. This system also identifies rank inconsistency based on the energy of each node. Hence, this approach enhances the secure routing in RPL based Internet of Things.