Walter Scott, Jr. College of Engineering

Graduate Exam Abstract

Divyanka Bose
M.S. Final
Jul 30, 2015, 1:00 pm - 3:00 pm
ECE Conference Room
Security of Virtual Coordinate based Wireless Sensor Networks
Abstract: Wireless Sensor Networks (WSNs)
perform critical functions in many
applications such as military surveillance,
rescue operations, detection of fires and
heath care monitoring. In these
applications, nodes in the network carry
critical and sensitive data. Thus, WSNs
are prone to various kinds of attacks that
target different protocols and layers of
the network. Also, most of the WSNs are
placed remotely that makes it difficult to
implement security measures after
deployment. Thus, security of WSNs
needs to be considered at the initial
stage of system design. In many
applications, the nodes are deployed
randomly, and thus are unpredictable in
terms of physical network topology.
Virtual Coordinate (VC) based WSNs
possess significant advantages over
Geographical Coordinate based WSNs.
This is because VCs negate the need for
physical localization of nodes, which
require costly techniques like GPS. The
VCs of the nodes in the network are very
important for basic functionalities such
as routing and self-organization.
However, security of VCs has not been
extensively researched even though
routing algorithms rely on the
correctness of the VCs for proper
functioning. VC based WSNs are
susceptible to attacks resulting from
malicious modification of VCs of
individual nodes. While the impact of
some such attacks is localized, others
such as coordinate deflation and
wormholes (tunneling) can cause severe
disruptions. This thesis proposes
techniques for the detection and
mitigation of attacks, which are aimed at
the Virtual Coordinate (VC) based WSNs.

We propose a novel approach where
coordinate attacks are identified by
detecting changes in shape of the
network, extracted using topology maps.
A comprehensive solution for detection
of coordinate-based attacks on VC
systems is presented that combines Beta
Reputation System and a reputation
based routing scheme. Latter ensures
safe communication that bypasses
malicious nodes during detection
process. The coordinate deflation and
wormhole attacks are discussed and the
effect and intensity of these attacks are
addressed. Two methods are proposed
and compared for the detection of
attacks. In the first method, the topology
distortion is rated using clusters
identifiable by existing VCs, thus
requiring low computation and
communication overhead. A measure of
topology distortion is presented. The
existence of a trusted base station is
needed for this method. In the second
method, the detection is distributed and
removes the need for a base
station/server. We compare the
advantages and disadvantages of the
two methods, and discuss the scenarios
in which these algorithms maybe

Simulation based evaluations
demonstrate that both the schemes
efficiently detects deflation and
wormhole attacks. We choose a variety
of dense networks with different
topologies and deployment
characteristics for evaluation. Networks
with voids, representative of physical
spaces with voids, are considered, as
well as randomly deployed networks to
ensure the correct operation and
scalability of the algorithms. We show
through simulations that the detection
schemes can easily differentiate between
the changes in the network due to node
failures, e.g., caused by battery drain,
from those due to an attack. Future
sensor networks are predicted to be in
the scale of millions of nodes. Thus, a
need for security algorithms which can
be scaled are highly desirable. We show
in our simulations that the proposed
detection schemes can be applied to
networks of larger density successfully.
Adviser: Dr. Anura Jayasumana
Co-Adviser: N/A
Non-ECE Member: Dr. Christos Papadopoulos
Member 3: Dr. Sudeep Pasricha
Addional Members: N/A
D. Bose and A. P. Jayasumana, "A Reputation-Based Method for Detection of Attacks in Virtual Coordinate Based Wireless Sensor Networks," In Proceedings of 40th Annual IEEE Conference on Local Computer Networks(LCN), Oct 2015
Program of Study: