STARS: A STATISTICAL
TRAFFIC PATTERN DISCOVERY SYSTEM FOR MANETS
ABSTRACT:
Many
anonymity enhancing techniques have been proposed based on packet encryption to
protect the communication anonymity of mobile ad hoc networks (MANETs).
However, in this paper, we show that MANETs are still vulnerable under passive statistical
traffic analysis attacks. To demonstrate how to discover the communication
patterns without decrypting the captured packets, we present a novel
statistical traffic pattern discovery system (STARS). STARS works passively to
perform traffic analysis based on statistical characteristics of captured raw
traffic. STARS are capable of discovering the sources, the destinations, and
the end-to-end communication relations. Empirical studies demonstrate that
STARS achieves good accuracy in disclosing the hidden traffic patterns.
EXISTING SYSTEM:
Over
the past few decades, traffic analysis models have been widely investigated for
static wired networks. For example, the simplest approach to track a message is
to enumerate all possible links a message could traverse, namely, the brute
force approach. Recently, statistical traffic analysis attacks have attracted broad
interests due to their passive nature, i.e., attackers only need to collect
information and perform analysis quietly without changing the network behavior
(such as injecting or modifying packets). The predecessor attacks and
disclosure attacks are two representatives. However, all these previous
approaches do not work.
DISADVANTAGES OF EXISTING
SYSTEM:
v It
is difficult to identify the sources or the destinations of the network flows.
v It
is difficult to identify the end -to- end communication relations.
PROPOSED
SYSTEM:
In
this paper, we propose a novel statistical traffic pattern discovery system (STARS).
STARS aims to derive the source/destination probability distribution, i.e., the
probability for each node to be a message source/destination, and the
end-to-end link probability distribution, i.e., the probability for each pair
of nodes to be an end-to-end communication pair. To achieve its goals, STARS
includes two major steps: 1) Construct point-to-point traffic matrices using
the time-slicing technique, and then derive the end-to-end traffic matrix with
a set of traffic filtering rules; and 2) Apply a heuristic approach to identify
the actual source and destination nodes, and then correlate the source nodes
with their corresponding destinations.
ADVANTAGES OF PROPOSED
SYSTEM:
v
It divides the entire network into
multiple regions geographically.
v
Deploy sensors along the boundaries of
each region to monitor the cross-component traffic.
v
Analyze the traffic even when nodes are
close to each other by treating the close nodes as a super node.
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 : .Net
Data
Base : SQL Server 2005
Tool : VISUAL STUDIO 2008.
REFERENCE:
Yang
Qin, Dijiang Huang, Senior Member, IEEE, and Bing Li, Student Member, IEEE, “STARS: A Statistical Traffic Pattern Discovery
System for MANETs” Yang Qin, Dijiang Huang, Senior Member, IEEE, and Bing
Li, Student Member, IEEE
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