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 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.
EXISTING SYSTEM:
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.
PROPOSED SYSTEM:
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.
SYSTEM CONFIGURATION:-
HARDWARE REQUIREMENTS:-
Processor - Pentium –IV
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
SOFTWARE
REQUIREMENTS:
Operating
system : Windows XP.
Coding
Language : JAVA
Data
Base : SQL
Tool : Netbeans
REFERENCE:
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
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