یادداشتهای مربوط به کتابنامه ، واژه نامه و نمایه های داخل اثر
متن يادداشت
Includes bibliographical references and index.
یادداشتهای مربوط به مندرجات
متن يادداشت
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].
متن يادداشت
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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یادداشتهای مربوط به خلاصه یا چکیده
متن يادداشت
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.