Efficient Intrusion Detection in P2P IoT Networks.

Abstract

We study efficient and lightweight Intrusion Detection Systems for Ad-Hoc networks via the prism of IPv6- enabled Wireless Sensor Networks. These networks consist of highly constrained devices organised in mesh networks following ad-hoc architectures, and as such carry specific characteristics that are not efficiently addressed by current state-of-the-art. In this work we first identify a trade-off between the communication and energy overhead of an IDS (as captured by the number of active IDS agents in the network) and the performance of the system in terms of successfully identifying attacks. In order to fine tune this trade-off, we first model such networks with the use of Random Geometric Graphs as this is a rigorous approach that allows us to capture underlying structural properties of the network. We then introduce a novel architectural approach for IDS by having only a subset of the nodes acting as IDS agents. These nodes are able to efficiently detect attacks at the networking layer in a collaborative manner by monitoring locally available network information provided by IoT routing protocols such as RPL. Our detailed experimental evaluation demonstrates significant performance gains in terms of communication overhead and energy dissipation while maintaining high detection rates.