We focus on detecting intrusions in wireless 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 present a polynomial complexity selection algorithm that attains a guaranteeable approximation bound. We also modify this algorithm to allow for seamless operation in time varying topologies, and evaluate the efficacy of the approximation algorithm and its modifications using simulation. We identify a selection algorithm that attains a good balance between performance and complexity for attaining robust intrusion detection in ad hoc networks.