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Security of virtual coordinate based wireless sensor networks

Date

2015

Authors

Bose, Divyanka, author
Jayasumana, Anura, advisor
Pasricha, Sudeep, committee member
Papadopoulos, Christos, committee member

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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 (GC) 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 VC based WSNs. We propose a novel approach where coordinate attacks are identified by detecting changes in the 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 implemented. 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, as well as randomly deployed networks are considered, 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.

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