| Document Type
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BL
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| Record Number
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953410
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| Doc. No
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b707780
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| Title & Author
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Privacy-preserving data mining : : models and algorithms /\ edited by Charu C. Aggarwal and Philip S. Yu.
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| Publication Statement
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New York :: Springer,, ©2008.
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| Series Statement
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Advances in database systems ;; v. 34
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| Page. NO
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1 online resource (xxii, 513 pages) :: illustrations
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| ISBN
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0387709916
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: 0387709924
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: 9780387709918
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: 9780387709925
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| Bibliographies/Indexes
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Includes bibliographical references and index.
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| Contents
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A survey of association rule hiding methods for privacy / Vassilios S. Verykios and Aris Gkoulalas-Divanis -- A survey of statistical approaches to preserving confidentiality of contigency table entries / Stephen E. Fienberg and Aleksandra B. Slavkovic -- A survey of privacy-preserving methods across horizontally partitioned data / Murat Kantarcioglu -- A survey of privacy-preserving methods across vertically partitioned data / Jaideep Vaidya -- A survey of attack techniques on privacy-preserving data perturbation methods / Kun Liu, Chris Giannella, and Hillol Kargupta -- Private data analysis via output perturbation / Kobbi Nissim -- A survey of query auditing techniques for data privacy / Shubha U. Nabar [and others] -- Privacy and the dimensionality curse / Charu C. Aggarwal -- Personalized privacy preservation / Yufei Tao and Xiaokui Xiao -- Privacy-preserving data stream classification / Yabo Xu [and others].
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An introduction to privacy-preserving data mining / Charu C. Aggarwal, Philip S. Yu -- A general survey of privacy-preserving data mining models and algorithms / Charu C. Aggarwal, Philip S. Yu -- A survey of inference control methods for privacy-preserving data mining / Josep Domingo-Ferrer -- Measures of anonymity / Suresh Venkatasubramanian -- k-Anonymous data mining : a survey / V. Ciriani [and others] -- A survey of randomization methods for privacy-preserving data mining / Charu C. Aggarwal, Philip S. Yu -- A survey of multiplicative perturbation for privacy-preserving data mining / Keke Chen and Ling Liu -- A survey of quantification of privacy preserving data mining algorithms / Elisa Bertino, Dan Lin and Wei Jiang -- A survey of utility-based privacy-preserving data transformation models / Ming Hua and Jian Pei -- Mining association rules under privacy constraints / Jayant R. Haritsa.
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| Abstract
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Advances in hardware technology have increased the capability to store and record personal data about consumers and individuals. This has caused concerns that personal data may be used for a variety of intrusive or malicious purposes. Privacy Preserving Data Mining: Models and Algorithms proposes a number of techniques to perform the data mining tasks in a privacy-preserving way. These techniques generally fall into the following categories: data modification techniques, cryptographic methods and protocols for data sharing, statistical techniques for disclosure and inference control, query auditing methods, randomization and perturbation-based techniques. This edited volume also contains surveys by distinguished researchers in the privacy field. Each survey includes the key research content as well as future research directions of a particular topic in privacy. Privacy Preserving Data Mining: Models and Algorithms is designed for researchers, professors, and advanced-level students in computer science. This book is also suitable for practitioners in industry.
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| Subject
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Computer security.
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Data mining.
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Data protection.
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Computer security.
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COMPUTERS-- Database Management-- Data Mining.
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Data mining.
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Data protection.
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Informatique.
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Computer security.
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Data mining.
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| Subject
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Data protection.
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| Dewey Classification
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005.74 22
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| LC Classification
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QA76.9.D343P75 2008eb
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| NLM classification
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TP309. 2clc
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| Added Entry
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Aggarwal, Charu C.
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Yu, Philip S.
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