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Quantifying location privacy leakage from transaction prices

Gervais, Arthur; Ritzdorf, Hubert; Lucic, Mario; Lenders, Vincent; Capkun, Srdjan; (2016) Quantifying location privacy leakage from transaction prices. In: Askoxylakis, Ioannis and Ioannidis, Sotiris and Katsikas, Sokratis and Meadows, Catherine, (eds.) ESORICS 2016: Computer Security – ESORICS 2016. (pp. pp. 382-405). Springer: Cham, Switzerland. Green open access

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Abstract

Large-scale datasets of consumer behavior might revolutionize the way we gain competitive advantages and increase our knowledge in the respective domains. At the same time, valuable datasets pose potential privacy risks that are difficult to foresee. In this paper we study the impact that the prices from consumers’ purchase histories have on the consumers’ location privacy. We show that using a small set of low-priced product prices from the consumers’ purchase histories, an adversary can determine the country, city, and local retail store where the transaction occurred with high confidence. Our paper demonstrates that even when the product category, precise time of purchase, and currency are removed from the consumers’ purchase history (e.g., for privacy reasons), information about the consumers’ location is leaked. The results are based on three independent datasets containing thousands of low-priced and frequently-bought consumer products. The results show the existence of location privacy risks when releasing consumer purchase histories. As such, the results highlight the need for systems that hide transaction details in consumer purchase histories.

Type: Proceedings paper
Title: Quantifying location privacy leakage from transaction prices
Event: European Symposium on Research in Computer Security ESORICS 2016
Open access status: An open access version is available from UCL Discovery
DOI: 10.1007/978-3-319-45741-3_20
Publisher version: https://doi.org/10.1007/978-3-319-45741-3_20
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.
Keywords: Mutual Information, Product Category, Location Privacy, Privacy Risk, Store Chain
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/10182348
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