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Computer Science - Security and Cryptology | Privacy, Security, and Trust in KDD - Second ACM SIGKDD International Workshop, PinKDD 2008, Las

Privacy, Security, and Trust in KDD

Second ACM SIGKDD International Workshop, PinKDD 2008, Las Vegas, Nevada, August 24, 2008, Revised Selected Papers

Bonchi, F., Ferrari, E., Jiang, W., Malin, B. (Eds.)

2009, IX, 127 p.

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This book constitutes the thoroughly refereed post-workshop proceedings of the Second International Workshop on Privacy, Security, and Trust in KDD, PinKDD 2008, held in Las Vegas, NV, USA, in March 2008 in conjunction with the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2008.

The 5 revised full papers presented together with 1 invited keynote lecture and 2 invited panel sessions were carefully reviewed and selected from numerous submissions. The papers are extended versions of the workshop presentations and incorporate reviewers' comments and discussions at the workshop and represent the diversity of data mining research issues in privacy, security, and trust as well as current work on privacy issues in geographic data mining.

Content Level » Research

Keywords » access control - anonymization - classification - data analysis - data mining - fraud detection - geocoding - graph data - identification - intelligence informatics - knowledge discovery - modeling - national security - network security - privacy

Related subjects » Communication Networks - Database Management & Information Retrieval - General Issues - Security and Cryptology

Table of contents 

Invited Paper.- Data Mining for Security Applications and Its Privacy Implications.- Geocode Matching and Privacy Preservation.- Mobility, Data Mining and Privacy the Experience of the GeoPKDD Project.- Contributed Papers.- Data and Structural k-Anonymity in Social Networks.- Composing Miners to Develop an Intrusion Detection Solution.- Malicious Code Detection Using Active Learning.- Maximizing Privacy under Data Distortion Constraints in Noise Perturbation Methods.- Strategies for Effective Shilling Attacks against Recommender Systems.

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