Toward
a Statistical Framework for Source Anonymity in Sensor Networks
ABSTRACT:
In certain applications, the locations of events
reported by a sensor network need to remain anonymous. That is, unauthorized
observers must be unable to detect the origin of such events by analyzing the
network traffic. Known as the source anonymity problem, this problem has
emerged as an important topic in the security of wireless sensor networks, with
variety of techniques based on different adversarial assumptions being proposed.
In this work, we present a new framework for modeling, analyzing, and
evaluating anonymity in sensor networks. The novelty of the proposed framework
is twofold: first, it introduces the notion of “interval indistinguishability”
and provides a quantitative measure to model anonymity in wireless sensor
networks; second, it maps source anonymity to the statistical problem of binary
hypothesis testing with nuisance parameters. We then analyze existing solutions
for designing anonymous sensor networks using the proposed model. We show how
mapping source anonymity to binary hypothesis testing with nuisance parameters
leads to converting the problem of exposing private source information into
searching for an appropriate data transformation that removes or minimize the
effect of the nuisance information. By doing so, we transform the problem from
analyzing real-valued sample points to binary codes, which opens the door for
coding theory to be incorporated into the study of anonymous sensor networks.
Finally, we discuss how existing solutions can be modified to improve their
anonymity.
ARCHITECTURE:
EXISTING SYSTEM:
While transmitting the “description” of a sensed
event in a private manner can be achieved via encryption primitives, hiding the
timing and spatial information of reported events cannot be achieved via
cryptographic means.
Encrypting a message before transmission, for
instance, can hide the context of the message from unauthorized observers, but
the mere existence of the ciphertext is indicative of information transmission.
In the existing literature, the source anonymity
problem has been addressed under two different types of adversaries, namely,
local and global adversaries. A local adversary is defined to be an adversary
having limited mobility and partial view of the network traffic. Routing based techniques
have been shown to be effective in hiding the locations of reported events
against local adversaries.
A global adversary is defined to be an adversary
with ability to monitor the traffic of the entire network (e.g., coordinating
adversaries spatially distributed over the network). Against global
adversaries, routing based techniques are known to be ineffective in concealing
location information in event-triggered transmission. This is due to the fact
that, since a global adversary has full spatial view of the network, it can
immediately detect the origin and time of the event-triggered transmission
DISADVANTAGES
OF EXISTING SYSTEM:
The source anonymity problem in wireless sensor networks
is the problem of studying techniques that provide time and location privacy
for events reported by sensor nodes. (Time and location privacy will be used
interchangeably with source anonymity throughout the paper.)
The source anonymity problem has been drawing
increasing research attention recently.
PROPOSED SYSTEM:
In this paper, we investigate the problem of
statistical source anonymity in wireless sensor networks. The main
contributions of this paper can be summarized by the following points.
We introduce the notion of “interval in-distinguishability”
and illustrate how the problem of statistical source anonymity can be mapped to
the problem of interval indistinguishability.
We propose a quantitative measure to evaluate statistical
source anonymity in sensor networks.
We map the problem of breaching source anonymity to
the statistical problem of binary hypothesis testing with nuisance parameters.
We demonstrate the significance of mapping the problem
in hand to a well-studied problem in uncovering hidden vulnerabilities. In
particular, realizing that the SSA problem can be mapped to the hypothesis
testing with nuisance parameters implies that breaching source anonymity can be
converted to finding an appropriate data transformation that removes the nuisance
information.
We analyze existing solutions under the proposed model.
By finding a transformation of observed data,we convert the problem from
analyzing real-valued samples to binary codes and identify a possible anonymity
breach in the current solutions for the SSA problem.
We pose and answer the important research question of
why previous studies were unable to detect the possible anonymity breach
identified in this paper.
We discuss, by looking at the problem as a coding problem,
a new direction to enhance the anonymity of existing SSA solutions.
ADVANTAGES
OF PROPOSED SYSTEM:
Removes or minimize the effect of the nuisance
information
SYSTEM CONFIGURATION:-
HARDWARE CONFIGURATION:-
ü Processor - Pentium –IV
ü Speed - 1.1
Ghz
ü RAM - 256
MB(min)
ü Hard
Disk - 20
GB
ü Key
Board - Standard
Windows Keyboard
ü Mouse - Two
or Three Button Mouse
ü Monitor - SVGA
SOFTWARE CONFIGURATION:-
ü Operating System : Windows XP
ü Programming Language : JAVA
ü Java Version : JDK 1.6 & above.
REFERENCE:
Basel Alomair, Member, IEEE, Andrew
Clark, Student Member, IEEE, Jorge Cuellar, and Radha Poovendran, Senior
Member, IEEE, “Toward a Statistical Framework for Source Anonymity in Sensor
Networks”, IEEE TRANSACTIONS ON MOBILE
COMPUTING, VOL. 12, NO. 2, FEBRUARY 2013.