Privacy, Security, and Trust in KDD: First ACM SIGKDD International Workshop, PinKDD 2007, San Jose, CA, USA, August 12, 2007, Revised Selected Papers

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This book constitutes the thoroughly refereed post-workshop proceedings of the First International Workshop on Privacy, Security, and Trust in KDD, PinKDD 2007, held in San Jose, CA, USA, in August 2007 in conjunction with the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2007.

The 8 revised full papers presented together with 1 keynote lecture were carefully reviewed and selected from numerous submissions. The papers address all prevailing topics concerning privacy, security, and trust aspects of data mining and knowledge discovery. Special focus is put on applied domains such as healthcare, ubiquitous computing, and location-based services.

Author(s): Cynthia Dwork (auth.), Francesco Bonchi, Elena Ferrari, Bradley Malin, YĆ¼cel Saygin (eds.)
Series: Lecture Notes in Computer Science 4890 : Information Systems and Applications, incl. Internet/Web, and HCI
Edition: 1
Publisher: Springer-Verlag Berlin Heidelberg
Year: 2008

Language: English
Pages: 173
Tags: Information Systems Applications (incl.Internet); Data Mining and Knowledge Discovery; Computer Communication Networks; Computers and Society; Legal Aspects of Computing; Management of Computing and Information Systems

Front Matter....Pages -
An Ad Omnia Approach to Defining and Achieving Private Data Analysis....Pages 1-13
Phoenix: Privacy Preserving Biclustering on Horizontally Partitioned Data....Pages 14-32
Allowing Privacy Protection Algorithms to Jump Out of Local Optimums: An Ordered Greed Framework....Pages 33-55
Probabilistic Anonymity....Pages 56-79
Website Privacy Preservation for Query Log Publishing....Pages 80-96
Privacy-Preserving Data Mining through Knowledge Model Sharing....Pages 97-115
Privacy-Preserving Sharing of Horizontally-Distributed Private Data for Constructing Accurate Classifiers....Pages 116-137
Towards Privacy-Preserving Model Selection....Pages 138-152
Preserving the Privacy of Sensitive Relationships in Graph Data....Pages 153-171
Back Matter....Pages -