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Privacy and Security Issues in Data Mining and Machine Learning - International ECML/PKDD Workshop, PSDML 2010, Barcelona, Spain, September 24, 2010. Revised Selected Papers (Paperback, Edition.)
Christos Dimitrakakis, Aris Gkoulalas-Divanis, Aikaterini Mitrokotsa, Vassilios S Verykios, Yucel Saygin
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R1,553
Discovery Miles 15 530
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Ships in 10 - 15 working days
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This book constitutes the refereed proceedings of the International
ECML/PKDD Workshop on Privacy and Security Issues in Data Mining
and Machine Learning, PSDML 2010, held in Barcelona, Spain, in
September 2010. The 11 revised full papers presented were carefully
reviewed and selected from 21 submissions. The papers range from
data privacy to security applications, focusing on detecting
malicious behavior in computer systems.
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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 (Paperback, 2008 ed.)
Francesco Bonchi, Elena Ferrari, Bradley Malin, Yucel Saygin
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R1,597
Discovery Miles 15 970
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Ships in 10 - 15 working days
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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.
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