Departmental Papers (ESE)


We focus on detecting intrusions in ad hoc networks using the misuse detection technique. We allow for detection modules that periodically fail to detect attacks and also generate false positives. Combining theories of hypothesis testing and approximation algorithms, we develop a framework to counter different threats while minimizing the resource consumption. We obtain computationally simple optimal rules for aggregating and thereby minimizing the errors in the decisions of the nodes executing the intrusion detection software (IDS) modules. But, we show that the selection of the optimal set of nodes for executing the IDS is an NP-hard problem. We describe a polynomial complexity, distributed selection algorithm, "Maximum Unsatisfied Neighbors in Extended Neighborhood" (MUNEN) that attains the best possible approximation ratio. The aggregation rules and MUNEN can be executed by mobile nodes with limited processing power. The overall framework provides a good balance between complexity and performance for attaining robust intrusion detection in ad hoc networks.

Document Type

Journal Article

Date of this Version

April 2006


Copyright 2006 IEEE. Reprinted from Proceedings of the 25th IEEE International Conference on Computer Communications (INFOCOM 2006), April 2006, 14 pages.

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Date Posted: 20 March 2008

This document has been peer reviewed.