Pyrgelis, A;
Troncoso, C;
Cristofaro, ED;
(2018)
Knock Knock, Who's There? Membership Inference on Aggregate Location Data.
In:
Proceedings of the 25th Network and Distributed System Security Symposium (NDSS 2018).
Internet Society: San Diego, CA, USA.
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Abstract
Aggregate location data is often used to support smart services and applications, such as generating live traffic maps or predicting visits to businesses. In this paper, we present the first study on the feasibility of membership inference attacks on aggregate location time-series. We introduce a game-based definition of the adversarial task, and cast it as a classification problem where machine learning can be used to distinguish whether or not a target user is part of the aggregates. We empirically evaluate the power of these attacks on both raw and differentially private aggregates using two real-world mobility datasets. We find that membership inference is a serious privacy threat, and show how its effectiveness depends on the adversary's prior knowledge, the characteristics of the underlying location data, as well as the number of users and the timeframe on which aggregation is performed. Although differentially private defenses can indeed reduce the extent of the attacks, they also yield a significant loss in utility. Moreover, a strategic adversary mimicking the behavior of the defense mechanism can greatly limit the protection they provide. Overall, our work presents a novel methodology geared to evaluate membership inference on aggregate location data in real-world settings and can be used by providers to assess the quality of privacy protection before data release or by regulators to detect violations.
Type: | Proceedings paper |
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Title: | Knock Knock, Who's There? Membership Inference on Aggregate Location Data |
Event: | 25th Network and Distributed System Security Symposium (NDSS 2018) |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.14722/ndss.2018.23183 |
Publisher version: | http://dx.doi.org/10.14722/ndss.2018.23183 |
Language: | English |
Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
URI: | https://discovery.ucl.ac.uk/id/eprint/10038879 |
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