Li-MSD: A lightweight mitigation solution for DAO insider attack in RPL-based IoT

TL;DR

This paper introduces Li-MSD, a lightweight blacklisting-based mitigation strategy that effectively counters DAO insider attacks in RPL-based IoT networks, restoring network performance in resource-constrained LLNs.

Contribution

Li-MSD is a novel, energy-efficient mitigation approach that outperforms existing solutions in defending against DAO insider attacks in RPL networks.

Findings

Li-MSD significantly reduces attack impact on network performance.

Li-MSD outperforms existing mitigation solutions in simulations.

The approach is suitable for resource-constrained IoT environments.

Abstract

Many IoT applications run on a wireless infrastructure supported by resource-constrained nodes which is popularly known as Low-Power and Lossy Networks (LLNs). Currently, LLNs play a vital role in digital transformation of industries. The resource limitations of LLNs restrict the usage of traditional routing protocols and therefore require an energy-efficient routing solution. IETF's Routing Protocol for Low-power Lossy Networks (RPL, pronounced 'ripple') is one of the most popular energy-efficient protocols for LLNs, specified in RFC 6550. In RPL, Destination Advertisement Object (DAO) control message is transmitted by a child node to pass on its reachability information to its immediate parent or root node. An attacker may exploit the insecure DAO sending mechanism of RPL to perform 'DAO insider attack' by transmitting DAO multiple times. This paper shows that an aggressive DAO insider attacker can drastically degrade network performance. We propose a Lightweight Mitigation Solution for DAO insider attack, which is termed as 'Li-MSD'. Li-MSD uses a blacklisting strategy to mitigate the attack and restore RPL performance, significantly. By using simulations, it is shown that Li-MSD outperforms the existing solution in the literature.