Privacy Risk for Individual Basket Patterns

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TitlePrivacy Risk for Individual Basket Patterns
Publication TypeConference Paper
Year of Publication2019
AuthorsPellungrini, R, Monreale, A, Guidotti, R
Secondary AuthorsAlzate, C, Monreale, A, Bioglio, L, Bitetta, V, Bordino, I, Caldarelli, G, Ferretti, A, Guidotti, R, Gullo, F, Pascolutti, S, Pensa, RG, Robardet, C, Squartini, T
Conference NameECML PKDD 2018 Workshops
Date Published2019//
PublisherSpringer International Publishing
Conference LocationCham
ISBN Number978-3-030-13463-1
AbstractRetail data are of fundamental importance for businesses and enterprises that want to understand the purchasing behaviour of their customers. Such data is also useful to develop analytical services and for marketing purposes, often based on individual purchasing patterns. However, retail data and extracted models may also provide very sensitive information to possible malicious third parties. Therefore, in this paper we propose a methodology for empirically assessing privacy risk in the releasing of individual purchasing data. The experiments on real-world retail data show that although individual patterns describe a summary of the customer activity, they may be successful used for the customer re-identifiation.
URLhttps://link.springer.com/chapter/10.1007/978-3-030-13463-1_11
DOI10.1007/978-3-030-13463-1_11
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