Wednesday, 23 July 2014
Real-Time Misbehavior Detection in IEEE 802.11-Based Wireless Networks: An Analytical Approach
REAL-TIME MISBEHAVIOR DETECTION IN IEEE 802.11-BASED WIRELESS NETWORKS: AN ANALYTICAL APPROACH
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 backoff parameters and, thus, unfairly gain a large share of the network throughput. In this paper, we first design a real-time backoff 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 backoff 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.
THE IEEE 802.11-based wireless local area networks (WLANs) have been widely deployed over recent years due to their high-speed access, easy-to-use features, and economical advantages. To resolve the contention issue among the multiple participating nodes, 802.11 employs the carrier sense multiple access/collision avoidance (CSMA/ CA) protocol to ensure that each node gets a reasonably fair share (FS) of the network. This is particularly the case for the distributed cooperation function (DCF) of 802.11, where every node accesses the network in a cooperative manner and randomly delays transmissions to avoid collisions by following a common backoff rule . However, in such a distributed environment without a centralized controller, a malicious node may deliberately choose a smaller backoff timer and selfishly gain an unfair share of the network throughput at the expenses of other normal nodes’ channel access opportunities. Moreover, only to make things worse, the easily available programmable and reconfigurable wireless network devices nowadays, make the backoff misbehavior much more feasible.
DISADVANTAGES OF EXISTING SYSTEM:
v It allows malicious nodes to deliberately manipulate their backoff parameters.
v It unfairly gain a large share of the network throughput.
To efficiently detect the backoff misbehavior, a detection scheme needs to address the two main correlated challenges: 1) unknown misbehavior strategy, 2) real-time detection of the misbehavior. For the first challenge, because a malicious node can first behave as a normal node and then manipulate its backoff timer to a random small value at any time, we have no way to know the misbehavior strategy a priori. For the second, the misbehavior needs to be detected in real time and we can then isolate the malicious node to prevent it from bringing more harm to the network as soon as possible. The existing solutions either cannot address both issues at the same time, or require modifications to the 802.11 protocols.
ADVANTAGES OF PROPOSED SYSTEM:
v Effective detector for real-time misbehavior detection
v To quickly find a selfish malicious node without any a priori knowledge of the statistics of the selfish misbehavior.
v Markov chain-based model to characterize the detection system.
Speed - 1.1 Ghz
RAM - 512 MB(min)
Hard Disk - 40 GB
Key Board - Standard Windows Keyboard
Mouse - Two or Three Button Mouse
Monitor - LCD/LED
Operating system : Windows XP.
Coding Language : JAVA
Data Base : SQL
Tool : Netbeans
Jin Tang, Member, IEEE, Yu Cheng, Senior Member, IEEE, and Weihua Zhuang, Fellow, IEEE, “Real-Time Misbehavior Detection in IEEE 802.11-Based Wireless Networks: An Analytical Approach” IEEE TRANSACTIONS ON MOBILE COMPUTING, VOL. 13, NO. 1, JANUARY 2014