Effective Privacy-Preserving Online Route Planning

TY - GEN

T1 - Effective Privacy-Preserving Online Route Planning

AU - Vicente, Carmen Ruiz

AU - Assent, Ira

AU - Jensen, Christian S.

PY - 2011

Y1 - 2011

N2 - An online Route Planning Service (RPS) computes a route from one location to another. Current RPSs such as Google Maps require the use of precise locations. However, some users may not want to disclose their source and destination locations due to privacy concerns. An approach that supplies fake locations to an existing service incurs a substantial loss of quality of service, and the service may well return a result that may be not helpful to the user. We propose a solution that is able to return accurate route planning results when source and destination regions are used in order to achieve privacy. The solution re-uses a standard online RPS rather than replicate this functionality, and it needs no trusted third party. The solution is able to compute the exact results without leaking of the exact locations to the RPS or un-trusted parties. In addition, we provide heuristics that reduce the number of times that the RPS needs to be queried, and we also describe how the accuracy and privacy requirements can be relaxed to achieve better performance. An empirical study offers insight into key properties of the approach.

AB - An online Route Planning Service (RPS) computes a route from one location to another. Current RPSs such as Google Maps require the use of precise locations. However, some users may not want to disclose their source and destination locations due to privacy concerns. An approach that supplies fake locations to an existing service incurs a substantial loss of quality of service, and the service may well return a result that may be not helpful to the user. We propose a solution that is able to return accurate route planning results when source and destination regions are used in order to achieve privacy. The solution re-uses a standard online RPS rather than replicate this functionality, and it needs no trusted third party. The solution is able to compute the exact results without leaking of the exact locations to the RPS or un-trusted parties. In addition, we provide heuristics that reduce the number of times that the RPS needs to be queried, and we also describe how the accuracy and privacy requirements can be relaxed to achieve better performance. An empirical study offers insight into key properties of the approach.

U2 - 10.1109/MDM.2011.20

DO - 10.1109/MDM.2011.20

M3 - Article in proceedings

SN - 978-1-4577-0581-6

SP - 119

EP - 128

BT - 2011 12th IEEE International Conference on Mobile Data Management (MDM)

PB - IEEE Computer Society Press

T2 - 12th IEEE International Conference on Mobile Data Management

Y2 - 6 June 2011 through 9 June 2011

ER -