TY - GEN

T1 - A Near-Optimal Source Location Privacy Scheme for Wireless Sensor Networks

AU - Bradbury, Matthew

AU - Jhumka, Arshad

PY - 2017/9/11

Y1 - 2017/9/11

N2 - 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.

AB - 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.

KW - Integer linear programming

KW - Monitoring

KW - Privacy

KW - Routing

KW - Routing protocols

KW - Wireless sensor networks

KW - Integer Linear Programming

KW - Optimal Routing

KW - Source Location Privacy

KW - Wireless Sensor Networks

U2 - 10.1109/Trustcom/BigDataSE/ICESS.2017.265

DO - 10.1109/Trustcom/BigDataSE/ICESS.2017.265

M3 - Conference contribution/Paper

SN - 97871509049066

SP - 409

EP - 416

BT - 2017 IEEE Trustcom/BigDataSE/ICESS

PB - IEEE

ER -