Privacy Preserving Data Mining [electronic resource] /
Vaidya, Jaideep.author.
Clifton, Christopher W.author.
Zhu, Yu Michael.author.
Data mining has emerged as a significant technology for gaining knowledge from vast quantities of data. However, concerns are growing that use of this technology can violate individual privacy. These concerns have led to a backlash against the technology, for example, a "Data-Mining Moratorium Act" introduced in the U.S. Senate that would have banned all data-mining programs (including research and development) by the U.S. Department of Defense. Privacy Preserving Data Mining provides a comprehensive overview of available approaches, techniques and open problems in privacy preserving data mining. This book demonstrates how these approaches can achieve data mining, while operating within legal and commercial restrictions that forbid release of data. Furthermore, this research crystallizes much of the underlying foundation, and inspires further research in the area. Privacy Preserving Data Mining is designed for a professional audience composed of practitioners and researchers in industry. This volume is also suitable for graduate-level students in computer science.
Description based upon print version of record.
Includes bibliographical references and index.
Privacy and Data Mining -- What is Privacy? -- Solution Approaches / Problems -- Predictive Modeling for Classification -- Predictive Modeling for Regression -- Finding Patterns and Rules (Association Rules) -- Descriptive Modeling (Clustering, Outlier Detection) -- Future Research - Problems remaining.
Data mining has emerged as a significant technology for gaining knowledge from vast quantities of data. However, concerns are growing that use of this technology can violate individual privacy. These concerns have led to a backlash against the technology, for example, a "Data-Mining Moratorium Act" introduced in the U.S. Senate that would have banned all data-mining programs (including research and development) by the U.S. Department of Defense. Privacy Preserving Data Mining provides a comprehensive overview of available approaches, techniques and open problems in privacy preserving data mining. This book demonstrates how these approaches can achieve data mining, while operating within legal and commercial restrictions that forbid release of data. Furthermore, this research crystallizes much of the underlying foundation, and inspires further research in the area. Privacy Preserving Data Mining is designed for a professional audience composed of practitioners and researchers in industry. This volume is also suitable for graduate-level students in computer science.
Data mining.
Database management.
Data structures (Computer science).
Data encryption (Computer science).
Information storage and retrieval.
Computer communication systems.
Data Mining and Knowledge Discovery.
Database Management.
Data Structures and Information Theory.
Cryptology.
Information Storage and Retrieval.
Computer Communication Networks.
Advances in Information Security