A mobile ad hoc network (MANET) is a collection of wireless devices moving in seemingly random directions and communicating with one another without the aid of an established infrastructure. To extend the reachability of a node, the other nodes in the network act as routers. Several intrusion detection techniques (IDTs) proposed for mobile ad hoc networks rely on each node passively monitoring the data forwarding by its next hop. This project presents quantitative evaluations of false positives and their impact on monitoring based intrusion detection for ad hoc networks. Experimental results show that, even for a simple three-node configuration, an actual ad hoc network suffers from high false positives; these results are validated by Markov and probabilistic models. However, this false positive problem cannot be observed by simulating the same network using popular ad hoc network simulators, such as ns-2, OPNET or Glomosim. To remedy this, a probabilistic noise generator model is implemented by using sliding window based monitoring approach. With this revised noise model, the simulated network exhibits the aggregate false positive behavior similar to that of the experimental testbed. Simulations of larger (50-node) ad hoc networks indicate that monitoring-based intrusion detection has very high false positives. These false positives can reduce the network performance or increase the overhead. In a simple monitoring-based system where no secondary and more accurate methods are used, the false positives impact the network performance in two ways: reduced throughput in normal networks without attackers and inability to mitigate the effect of attacks in networks with attackers.