NDLI: Hiding of User Presence for Privacy Preserving Data Mining

Content Provider	IEEE Xplore Digital Library
Author	Takenouchi, T. Kawamura, T. Ohsuga, A.
Copyright Year	2012
Abstract	Recently, it has been expected to realize privacy preserving data mining in order to acquire valuable knowledge from the combined information sources of several service providers. Therefore researches have been conducted on a distributed anonymization method, which combines the personal information and anonymize it to prevent identifying specific user records. However, in those researches, when sets of the users in the providers are not the same, there is a problem that users' presence in either provider may be revealed. Thus, this paper proposes a new indicator which represents the probability of the presence of users being revealed and introduces a modified distributed anonymization method to satisfy the proposed indicator. Also, we use U.S. census data for evaluation and calculate the relative error of its anonymized data. The results show that it is almost 10-25% in specific cases.
Starting Page	133
Ending Page	138
File Size	211574
Page Count	6
File Format	PDF
ISBN	9781467327190
DOI	10.1109/IIAI-AAI.2012.35
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-09-20
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Data privacy K-anonymity Distributed anonymization Protocols Accuracy Distributed databases Privacy Preserving Data Publishing Motion pictures Association rules Privacy Preserving Data Mining
Content Type	Text
Resource Type	Article

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