Mining Massive Data Sets for Security: Advances in Data Mining, Search, Social Networks and Text Mining, and Their Applications to Security - Volume . Information and Communication Security)

Fogelman-Soulie, F. & D. Perrotta & J. Piskorski & R. Steinberger

ISBN 10: 1586038982 / ISBN 13: 9781586038984

Verlag: IOS Press, Netherlands, 2008

Beschreibung

9.6 X 6.4 X 1.1 inches; 388 pages. Bestandsnummer des Verkäufers 8980

Bibliografische Details

Titel: Mining Massive Data Sets for Security: ...

Verlag: IOS Press, Netherlands

Erscheinungsdatum: 2008

Einband: Hardcover

Zustand: Very Good

Zustand des Schutzumschlags: No Dust Jacket

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Inhaltsangabe:

The real power for security applications will come from the synergy of academic and commercial research focusing on the specific issue of security. Special constraints apply to this domain, which are not always taken into consideration by academic research, but are critical for successful security applications: large volumes: techniques must be able to handle huge amounts of data and perform ‘on-line’ computation; scalability: algorithms must have processing times that scale well with ever growing volumes; automation: the analysis process must be automated so that information extraction can ‘run on its own’; ease of use: everyday citizens should be able to extract and assess the necessary information; and robustness: systems must be able to cope with data of poor quality (missing or erroneous data). The NATO Advanced Study Institute (ASI) on Mining Massive Data Sets for Security, held in Italy, September 2007, brought together around ninety participants to discuss these issues. This publication includes the most important contributions, but can of course not entirely reflect the lively interactions which allowed the participants to exchange their views and share their experience. The bridge between academic methods and industrial constraints is systematically discussed throughout. This volume will thus serve as a reference book for anyone interested in understanding the techniques for handling very large data sets and how to apply them in conjunction for solving security issues.