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Privacy, Security, and Trust in KDD: First ACM SIGKDD International Workshop, PinKDD 2007, San Jose, CA, USA, August 12, 2007, Revised, Selected Papers: 4890 (Lecture Notes in Computer Science, 4890) - Tapa blanda

Bonchi, Francesco

 
9783540784777: Privacy, Security, and Trust in KDD: First ACM SIGKDD International Workshop, PinKDD 2007, San Jose, CA, USA, August 12, 2007, Revised, Selected Papers: 4890 (Lecture Notes in Computer Science, 4890)
Tapa blanda
ISBN 10: 3540784772 ISBN 13: 9783540784777
Editorial: Springer Berlin Heidelberg, 2010

Sinopsis

Vast amounts of data are collected by service providers and system administ- tors, and are available in public information systems. Data mining technologies provide an ideal framework to assist in analyzing such collections for computer security and surveillance-related endeavors. For instance, system administrators can apply data mining to summarize activity patterns in access logs so that potential malicious incidents can be further investigated. Beyond computer - curity, data mining technology supports intelligence gathering and summari- tion for homeland security. For years, and most recently fueled by events such as September 11, 2001, government agencies have focused on developing and applying data mining technologies to monitor terrorist behaviors in public and private data collections. Theapplicationof data mining to person-speci?cdata raisesseriousconcerns regarding data con?dentiality and citizens’ privacy rights. These concerns have led to the adoption of various legislation and policy controls. In 2005, the - ropean Union passed a data-retention directive that requires all telephone and Internetservice providersto store data ontheir consumers for up to two yearsto assist in the prevention of terrorismand organized crime. Similar data-retention regulationproposalsareunderheateddebateintheUnitedStatesCongress. Yet, the debate often focuses on ethical or policy aspects of the problem, such that resolutions have polarized consequences; e. g. , an organization can either share data for data mining purposes or it can not. Fortunately, computer scientists, and data mining researchers in particular, have recognized that technology can beconstructedtosupportlesspolarizedsolutions. Computerscientistsaredev- oping technologies that enable data mining goals without sacri?cing the privacy and security of the individuals to whom the data correspond.

"Sinopsis" puede pertenecer a otra edición de este libro.

Reseña del editor

Vast amounts of data are collected by service providers and system administ- tors, and are available in public information systems. Data mining technologies provide an ideal framework to assist in analyzing such collections for computer security and surveillance-related endeavors. For instance, system administrators can apply data mining to summarize activity patterns in access logs so that potential malicious incidents can be further investigated. Beyond computer - curity, data mining technology supports intelligence gathering and summari- tion for homeland security. For years, and most recently fueled by events such as September 11, 2001, government agencies have focused on developing and applying data mining technologies to monitor terrorist behaviors in public and private data collections. Theapplicationof data mining to person-speci?cdata raisesseriousconcerns regarding data con?dentiality and citizens' privacy rights. These concerns have led to the adoption of various legislation and policy controls. In 2005, the - ropean Union passed a data-retention directive that requires all telephone and Internetservice providersto store data ontheir consumers for up to two yearsto assist in the prevention of terrorismand organized crime. Similar data-retention regulationproposalsareunderheateddebateintheUnitedStatesCongress. Yet, the debate often focuses on ethical or policy aspects of the problem, such that resolutions have polarized consequences; e. g. , an organization can either share data for data mining purposes or it can not. Fortunately, computer scientists, and data mining researchers in particular, have recognized that technology can beconstructedtosupportlesspolarizedsolutions. Computerscientistsaredev- oping technologies that enable data mining goals without sacri?cing the privacy and security of the individuals to whom the data correspond.

Reseña del editor

This book constitutes the thoroughly refereed post-workshop proceedings of the First International Workshop on Privacy, Security, and Trust in KDD, PinKDD 2007, held in San Jose, CA, USA, in August 2007 in conjunction with the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2007. The 8 revised full papers presented together with 1 keynote lecture were carefully reviewed and selected from numerous submissions. The papers address all prevailing topics concerning privacy, security, and trust aspects of data mining and knowledge discovery. Special focus is put on applied domains such as healthcare, ubiquitous computing, and location-based services.

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
Springer Berlin Heidelberg
Año de publicación
2010
Idioma
Inglés
ISBN 10 
3540784772
ISBN 13 
9783540784777
Encuadernación
Tapa blanda
Número de páginas
188
Contacto del fabricante
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