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Data for A near-optimal source location privacy scheme for wireless sensor networks
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Bradbury, Matthew S. and Jhumka, Arshad (2017) Data for A near-optimal source location privacy scheme for wireless sensor networks. [Dataset]
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Official URL: https://doi.org/10.5281/zenodo.801223
Abstract
As interest in using Wireless Sensor Networks (WSNs) for deployments in scenarios such as asset monitoring increases, the need to consider security and privacy issues also becomes greater. One such issue is that of Source Location Privacy (SLP) where the location of a source in the network needs to be kept secret from a malicious attacker. Many techniques have been proposed to provide SLP against an eavesdropping attacker. Most techniques work by first developing an algorithm followed by extensive performance validation. Differently, in this paper, we model the SLP problem as an Integer Linear Programming optimization problem. Using the IBM ILOG CPLEX optimiser, we obtain an optimal solution to provide SLP. However, that solution is centralised (i.e., requires network-wide knowledge) making the solution unsuitable for WSNs. Therefore, we develop a distributed version of the solution and evaluate the level of privacy provided by it. The solution is hybrid in nature, in that it uses both spatial and temporal redundancy to provide SLP. Results from extensive simulations using the TOSSIM WSN simulator indicate a 1% capture ratio is achievable as a trade-off for an increase in the delivery latency.
Item Type: | Dataset | ||||||
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Alternative Title: | ILP Routing Dataset | ||||||
Subjects: | Q Science > QA Mathematics T Technology > TK Electrical engineering. Electronics Nuclear engineering |
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Divisions: | Faculty of Science, Engineering and Medicine > Science > Computer Science | ||||||
Type of Data: | Experimental data | ||||||
Library of Congress Subject Headings (LCSH): | Wireless sensor networks -- Security measures, Routing (Computer network management) | ||||||
Publisher: | University of Warwick, Department of Computer Science | ||||||
Official Date: | 31 May 2017 | ||||||
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Status: | Not Peer Reviewed | ||||||
Publication Status: | Published | ||||||
Media of Output (format): | .txt | ||||||
Access rights to Published version: | Open Access (Creative Commons) | ||||||
Copyright Holders: | University of Warwick | ||||||
Description: | Data record consists of 119 data files in .txt format. |
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