DocumentCode
580158
Title
Privacy-preserving data mining demonstrator
Author
Beck, Martin ; Marhöfer, Michael
Author_Institution
Tech. Univ. Dresden, Dresden, Germany
fYear
2012
fDate
8-11 Oct. 2012
Firstpage
210
Lastpage
216
Abstract
We present a system for demonstrating anonymized data mining on user profiles, which also evaluates the remaining utility of the generalized information through comparison of the classification results. The use case for this scenario builds around profiles containing personally identifiable information, which should be analyzed and classified by a third party. Our goal is to preserve the privacy of the users while maintaining a certain level of utility to allow data mining over the anonymized information.
Keywords
data mining; data privacy; anonymized data mining; privacy-preserving data mining demonstrator; user privacy preservation; user profiles; Accuracy; Data models; Data privacy; Privacy; Runtime; Training; anonymization; data utility; demo; privacy preserving data mining;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligence in Next Generation Networks (ICIN), 2012 16th International Conference on
Conference_Location
Berlin
Print_ISBN
978-1-4673-1527-2
Electronic_ISBN
978-1-4673-1525-8
Type
conf
DOI
10.1109/ICIN.2012.6376028
Filename
6376028
Link To Document