Privacy-Preserving Data Mining:Models and Algorithms
Publication year: 2008
ISBN: 978-0-387-70992-5
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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.
Subject: Computer Science, DOM, Information, K-anonymity, algorithms, association rule hiding, classification, cryptographic approaches, data analysis, data mining, distributed priv, personalized privacy, privacy, query auditing, randonization, stream privacy, Systems and Data Security, Data Mining and Knowledge Discovery, Cryptology, Database Management, Information Storage and Retrieval, Information Systems Applications (incl. Internet)
