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Detection and labeling of personal identifiable information in E-mails

 
: Bier, Christoph; Prior, J.

:
Postprint urn:nbn:de:0011-n-3035899 (205 KByte PDF)
MD5 Fingerprint: eb929951f8081c322fd6bed9250f0b7d
The original publication is available at springerlink.com
Erstellt am: 06.06.2015


Cuppens-Boulahia, N. ; International Federation for Information Processing -IFIP-, Technical Committee Security and Privacy Protection in Information Processing Systems:
ICT systems security and privacy protection. 29th IFIP TC 11 International Conference, SEC 2014 : Marrakech, Morocco, June 2-4, 2014; Proceedings
Heidelberg: Springer, 2014 (IFIP advances in information and communication technology 428)
ISBN: 978-3-642-55414-8 (Print)
ISBN: 978-3-642-55415-5 (Online)
ISBN: 3-642-55414-8
S.351-358
International Information Security and Privacy Conference (SEC) <29, 2014, Marrakech>
Englisch
Konferenzbeitrag, Elektronische Publikation
Fraunhofer IOSB ()

Abstract
The protection of personal identifiable information (PII) is increasingly demanded by customers and data protection regulation. To safeguard PII a organization has to find out which incoming communication actually contains it. Only then PII can be labeled, tracked, and protected. E-mails are one of the main means of communication. They consist of unstructured data difficult to classify. We developed an automated detection system for PII in e-mails and connected it to a usage control infrastructure. Our concept is based on previous findings in the area of spam detection. We tested our approach with a data set in a customer service scenario. The evaluation shows that the utilization of Bayes-classification is very promising to detect PII.

: http://publica.fraunhofer.de/dokumente/N-303589.html