%0 Conference Paper %B ECML PKDD 2018 Workshops %D 2019 %T Privacy Risk for Individual Basket Patterns %A Roberto Pellungrini %A Anna Monreale %A Riccardo Guidotti %E Alzate, Carlos %E Anna Monreale %E Bioglio, Livio %E Bitetta, Valerio %E Bordino, Ilaria %E Caldarelli, Guido %E Ferretti, Andrea %E Riccardo Guidotti %E Gullo, Francesco %E Pascolutti, Stefano %E Pensa, Ruggero G. %E Robardet, CĂ©line %E Squartini, Tiziano %X 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. %B ECML PKDD 2018 Workshops %I Springer International Publishing %C Cham %8 2019// %@ 978-3-030-13463-1 %G eng %U https://link.springer.com/chapter/10.1007/978-3-030-13463-1_11 %R https://doi.org/10.1007/978-3-030-13463-1_11