Title
On the Application of SDC Stream Methods to Card Payments Analytics
Date Issued
01 January 2018
Access level
metadata only access
Resource Type
conference paper
Author(s)
Publisher(s)
Springer Nature
Abstract
Banks and financial services have to constantly innovate their online payment services to avoid large digital companies take the control of online card transactions, relegating traditional banks to simple payments carriers. Apart from creating new payment methods (e.g. contact-less cards, mobile wallets, etc.), banks offers new services based on historical payments data to endow traditional payments methods with new services and functionalities. In this latter case, it is where privacy preserving techniques play a fundamental role ensuring personal data is managed full-filling all the applicable laws and regulations. In this paper, we introduce some ideas about how SDC stream anonymization methods could be used to mask payments data streams. Besides, we also provide some experimental results over a real card payments database.
Start page
306
End page
318
Volume
11144 LNAI
Language
English
OCDE Knowledge area
Ciencias de la información
Ciencias de la computación
Subjects
Scopus EID
2-s2.0-85055678503
Source
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Resource of which it is part
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN of the container
03029743
ISBN of the container
9783030002015
Conference
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Sources of information:
Directorio de Producción Científica
Scopus