Distributed combined authentication and intrusion detection with data fusion in high security mobile ad-hoc networks

Abstract

This paper studies distributed, combined authentication and intrusion detection with data fusion in mobile ad-hoc networks (MANETs). Multimodal biometrics are deployed to work with intrusion detection systems (IDSs) to alleviate the shortcomings of unimodal biometric systems. Since each device in the network has measurement and estimation errors, more than one device needs to be chosen, and observations can be fused to increase observation accuracy using Dempster-Shafer theory for data fusion. The system decides whether or not user authentication (or IDS input) is required, and which biosensors (or IDSs) should be chosen depending on the security posture. The decisions are made in a fully distributed manner by each authentication device and each IDS. Simulation results are presented to show the effectiveness of the proposed scheme.