Thought off-line sanitization methods for bank transactions

Isaias Hoyos, Miguel Nunez-del-Prado

Resultado de la investigación: Capítulo del libro/informe/acta de congresoCapítulo de libro

Resumen

In the digital era, people generate a lot of digital traces ranging from posts on social networks, call detail records and credit or debit banks transactions among others. These data could help society to understand different urban phenomena such as what citizens are talking about, how they commute or what are their spending behaviors. Therefore, the use of such data trigger privacy issues. In the present effort, we study four different Statistical Disclosure Control filters to sanitize off-line credit or debit bank transactions. Consequently, we analyze Noise Addition, Microaggregation, Rank Swapping and Differential Privacy filters concerning Disclosure Risk, Information Loss, and utility. We observed that Microaggregation and Different Privacy perform very well for minimizing Disclosure Risk while providing a good utility for statistics of spending amounts per industry type.
Idioma originalInglés
Título de la publicación alojadaCommunications in Computer and Information Science
Páginas257-264
Número de páginas8
ISBN (versión digital)9783030116798
DOI
EstadoPublicada - 1 ene. 2019
EventoCommunications in Computer and Information Science -
Duración: 1 ene. 2019 → …

Serie de la publicación

NombreCommunications in Computer and Information Science
Volumen898
ISSN (versión impresa)1865-0929

Conferencia

ConferenciaCommunications in Computer and Information Science
Período1/01/19 → …

Palabras clave

  • Differential Privacy
  • Microaggregation
  • Privacy filters
  • Statistical Disclosure Control (SDC)

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