Robust detection of selfish misbehavior in wireless networks

The CSMA/CA protocols are designed under the assumption that all participant nodes would abide to the protocol rules. This is of particular importance in distributed protocols such as the IEEE 802.11 distributed coordinating function (DCF), in which nodes control their own backoff parameters. In this work, we propose a method to detect selfish misbehaving terminals that may deliberately modify its backoff window to gain unfair access to the network resources. We develop nonparametric batch and sequential detectors based on the Kolmogorov-Smirnov (K-S) statistics that do not require any modification on the existing CSMA/CA protocols, and we apply it to detect misbehaviors in an IEEE 802.11 DCF network using the ns-2 simulator. We compare the performance of the proposed detectors with the optimum detectors with perfect information about the misbehavior strategy, for both the batch case (based on the Neyman-Pearson test), and the sequential case (based on Wald's sequential probability ratio test). We show that the proposed nonparametric detectors have a performance comparable to the optimum detectors for the majority of misbehaviors (the more severe) without any knowledge of the misbehavior strategies.