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Book
Privacy-Preserving Data Mining : Models and Algorithms
Authors: ---
ISBN: 1281491713 9786611491710 0387709924 0387709916 Year: 2008 Publisher: New York, NY : Springer US : Imprint: Springer,

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Abstract

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. .

Keywords

Data mining. --- Computer security. --- Computer privacy --- Computer system security --- Computer systems --- Computers --- Cyber security --- Cybersecurity --- Electronic digital computers --- Protection of computer systems --- Security of computer systems --- Data protection --- Security systems --- Hacking --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Protection --- Security measures --- Data encryption (Computer science). --- Database management. --- Information storage and retrieva. --- Systems and Data Security. --- Data Mining and Knowledge Discovery. --- Cryptology. --- Database Management. --- Information Storage and Retrieval. --- Information Systems Applications (incl. Internet). --- Data base management --- Data services (Database management) --- Database management services --- DBMS (Computer science) --- Generalized data management systems --- Services, Database management --- Systems, Database management --- Systems, Generalized database management --- Electronic data processing --- Data encoding (Computer science) --- Encryption of data (Computer science) --- Computer security --- Cryptography --- Information storage and retrieval systems. --- Automatic data storage --- Automatic information retrieval --- Automation in documentation --- Computer-based information systems --- Data processing systems --- Data storage and retrieval systems --- Discovery systems, Information --- Information discovery systems --- Information processing systems --- Information retrieval systems --- Machine data storage and retrieval --- Mechanized information storage and retrieval systems --- Electronic information resources --- Data libraries --- Digital libraries --- Information organization --- Information retrieval --- Information storage and retrieval. --- Application software. --- Application computer programs --- Application computer software --- Applications software --- Apps (Computer software) --- Computer software


Digital
Privacy-Preserving Data Mining : Models and Algorithms
Authors: ---
ISBN: 9780387709925 Year: 2008 Publisher: Boston, MA Springer Science+Business Media, LLC


Book
Privacy-Preserving Data Mining : Models and Algorithms
Authors: --- ---
ISBN: 9780387709925 Year: 2008 Publisher: Boston MA Springer US

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Export citation

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Bookmark

Abstract

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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