TY - CONF T1 - Privacy Risk for Individual Basket Patterns T2 - ECML PKDD 2018 Workshops Y1 - 2019 A1 - Roberto Pellungrini A1 - Anna Monreale A1 - Riccardo Guidotti ED - Alzate, Carlos ED - Anna Monreale ED - Bioglio, Livio ED - Bitetta, Valerio ED - Bordino, Ilaria ED - Caldarelli, Guido ED - Ferretti, Andrea ED - Riccardo Guidotti ED - Gullo, Francesco ED - Pascolutti, Stefano ED - Pensa, Ruggero G. ED - Robardet, CĂ©line ED - Squartini, Tiziano AB - Retail 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. JF - ECML PKDD 2018 Workshops PB - Springer International Publishing CY - Cham SN - 978-3-030-13463-1 UR - https://link.springer.com/chapter/10.1007/978-3-030-13463-1_11 ER -