{"@context":{"@vocab":"https://cir.nii.ac.jp/schema/1.0/","rdfs":"http://www.w3.org/2000/01/rdf-schema#","dc":"http://purl.org/dc/elements/1.1/","dcterms":"http://purl.org/dc/terms/","foaf":"http://xmlns.com/foaf/0.1/","prism":"http://prismstandard.org/namespaces/basic/2.0/","cinii":"http://ci.nii.ac.jp/ns/1.0/","datacite":"https://schema.datacite.org/meta/kernel-4/","ndl":"http://ndl.go.jp/dcndl/terms/","jpcoar":"https://github.com/JPCOAR/schema/blob/master/2.0/"},"@id":"https://cir.nii.ac.jp/crid/1363670319497823232.json","@type":"Article","productIdentifier":[{"identifier":{"@type":"DOI","@value":"10.1126/science.1256297"}},{"identifier":{"@type":"URI","@value":"https://www.science.org/doi/pdf/10.1126/science.1256297"}}],"dc:title":[{"@value":"Unique in the shopping mall: On the reidentifiability of credit card metadata"}],"description":[{"type":"abstract","notation":[{"@value":"<jats:p>Large-scale data sets of human behavior have the potential to fundamentally transform the way we fight diseases, design cities, or perform research. Metadata, however, contain sensitive information. Understanding the privacy of these data sets is key to their broad use and, ultimately, their impact. We study 3 months of credit card records for 1.1 million people and show that four spatiotemporal points are enough to uniquely reidentify 90% of individuals. We show that knowing the price of a transaction increases the risk of reidentification by 22%, on average. Finally, we show that even data sets that provide coarse information at any or all of the dimensions provide little anonymity and that women are more reidentifiable than men in credit card metadata.</jats:p>"}]}],"creator":[{"@id":"https://cir.nii.ac.jp/crid/1383670319497823233","@type":"Researcher","foaf:name":[{"@value":"Yves-Alexandre de Montjoye"}],"jpcoar:affiliationName":[{"@value":"Media Lab, Massachusetts Institute of Technology (MIT), 20 Amherst Street, Cambridge, MA 02139, USA."}]},{"@id":"https://cir.nii.ac.jp/crid/1383670319497823235","@type":"Researcher","foaf:name":[{"@value":"Laura Radaelli"}],"jpcoar:affiliationName":[{"@value":"Department of Computer Science, Aarhus University, Aabogade 34, Aarhus, 8200, Denmark."}]},{"@id":"https://cir.nii.ac.jp/crid/1383670319497823232","@type":"Researcher","foaf:name":[{"@value":"Vivek Kumar Singh"}],"jpcoar:affiliationName":[{"@value":"Media Lab, Massachusetts Institute of Technology (MIT), 20 Amherst Street, Cambridge, MA 02139, USA."},{"@value":"School of Communication and Information, Rutgers University, 4 Huntington Street, New Brunswick, NJ 08901, USA."}]},{"@id":"https://cir.nii.ac.jp/crid/1383670319497823234","@type":"Researcher","foaf:name":[{"@value":"Alex “Sandy” Pentland"}],"jpcoar:affiliationName":[{"@value":"Media Lab, Massachusetts Institute of Technology (MIT), 20 Amherst Street, Cambridge, MA 02139, USA."}]}],"publication":{"publicationIdentifier":[{"@type":"PISSN","@value":"00368075"},{"@type":"EISSN","@value":"10959203"}],"prism:publicationName":[{"@value":"Science"}],"dc:publisher":[{"@value":"American Association for the Advancement of Science (AAAS)"}],"prism:publicationDate":"2015-01-30","prism:volume":"347","prism:number":"6221","prism:startingPage":"536","prism:endingPage":"539"},"reviewed":"false","dc:rights":["http://www.sciencemag.org/about/science-licenses-journal-article-reuse"],"url":[{"@id":"https://www.science.org/doi/pdf/10.1126/science.1256297"}],"createdAt":"2015-01-29","modifiedAt":"2024-01-10","relatedProduct":[{"@id":"https://cir.nii.ac.jp/crid/1050858441648899328","@type":"Article","resourceType":"学術雑誌論文(journal article)","relationType":["isReferencedBy"],"jpcoar:relatedTitle":[{"@language":"en","@value":"Re-Identification in Differentially Private Incomplete Datasets"}]},{"@id":"https://cir.nii.ac.jp/crid/1360857593801369216","@type":"Article","resourceType":"学術雑誌論文(journal article)","relationType":["isReferencedBy"],"jpcoar:relatedTitle":[{"@value":"Social physics"}]},{"@id":"https://cir.nii.ac.jp/crid/1390298668092704640","@type":"Article","resourceType":"学術雑誌論文(journal article)","relationType":["isReferencedBy"],"jpcoar:relatedTitle":[{"@language":"en","@value":"Frameworks for Privacy-Preserving Federated Learning"}]},{"@id":"https://cir.nii.ac.jp/crid/1390848250124885376","@type":"Article","relationType":["isReferencedBy"],"jpcoar:relatedTitle":[{"@language":"en","@value":"An Overview of De-Identification Techniques and Their Standardization Directions"}]}],"dataSourceIdentifier":[{"@type":"CROSSREF","@value":"10.1126/science.1256297"},{"@type":"CROSSREF","@value":"10.1109/ojcs.2022.3175999_references_DOI_OrKvLCJ8CTBy753S3YWN8YXHNyd"},{"@type":"CROSSREF","@value":"10.1587/transinf.2023mui0001_references_DOI_OrKvLCJ8CTBy753S3YWN8YXHNyd"},{"@type":"CROSSREF","@value":"10.1016/j.physrep.2021.10.005_references_DOI_OrKvLCJ8CTBy753S3YWN8YXHNyd"},{"@type":"CROSSREF","@value":"10.1587/transinf.2019ici0002_references_DOI_OrKvLCJ8CTBy753S3YWN8YXHNyd"}]}