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REAL-TIME MISBEHAVIOR DETECTION IN IEEE 802.11-BASED WIRELESS NETWORKS:

AN ANALYTICAL APPROACH

ABSTRACT

The distributed nature of the CSMA/CA-based wireless protocols, for example, the IEEE 802.11 distributed coordinated function (DCF), allows malicious nodes to deliberately manipulate their back off parameters and, thus, unfairly gain a large share of the network throughput. In this paper, we first design a real-time back off misbehavior detector, termed as the fair share detector (FS detector), which exploits the nonparametric cumulative sum (CUSUM) test to quickly find a selfish malicious node without any a priori knowledge of the statistics of the selfish misbehavior. While most of the existing schemes for selfish misbehavior detection depend on heuristic parameter configuration and experimental performance evaluation, we develop a Markov chain-based analytical model to systematically study the performance of the FS detector in real-time back off misbehavior detection. Based on the analytical model, we can quantitatively compute the system configuration parameters for guaranteed performance in terms of average false positive rate, average detection delay, and missed detection ratio under a detection delay constraint. We present thorough simulation results to confirm the accuracy of our theoretical analysis as well as demonstrate the performance of the developed FS detector.

EXISTING SYSTEM	PROPOSED SYSTEM
EXISTING CONCEPT:- Detecting misbehavior in the network is measuring configuration of the system as well as performance of the systems. Selfish misbehavior detection depends on heuristic parameter configuration and experimental performance evaluation.	PROPOSED CONCEPT:- FS detector exploits the nonparametric cumulative sum test to quickly find a selfish malicious node without any a priori knowledge of the statistics of the selfish misbehavior. Average false positive rate, average detection delay, and missed detection ratio metrics used in FS detector.
EXISTING TECHNIQUE:- Sequential Probability Ratio Test.	PROPOSED TECHNIQUE:- Fair Share Detector.
TECHNIQUE DEFINITION:- The model generates probabilistic proofs of possession.	TECHNIQUE DEFINITION:- The FS detector newly developed in this paper takes each successful transmission over the network as its observation sample.
DRAWBACKS:- Very difficult to know the back off behavior in the network. Hard to achieve in practice because the transmission attempts involved in a collision are impossible to be distinguished.	ADVANTAGES:- Easy to know the back off behavior in the network using FS detector. We monitor the successful transmission of the tagged node as the observation measurement.