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Autor(en): 
  • Jaideep Vaidya
  • Yu Michael Zhu
  • Christopher W Clifton
  • Privacy Preserving Data Mining 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 2 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   i.d.R. innert 14-24 Tagen versandfertig
    Veröffentlichung:  November 2005  
    Genre:  EDV / Informatik 
     
    Algorithmen und Datenstrukturen / Computers - Data Base Management / COMPUTERS / Computer Science / COMPUTERS / Databases / Data Mining / COMPUTERS / Databases / General / COMPUTERS / Information Theory / COMPUTERS / Networking / Hardware / COMPUTERS / Security / Cryptography
    ISBN:  9780387258867 
    EAN-Code: 
    9780387258867 
    Verlag:  Springer Us 
    Einband:  Gebunden  
    Sprache:  English  
    Serie:  Advances in Information Security  
    Dimensionen:  H 243 mm / B 164 mm / D 15 mm 
    Gewicht:  354 gr 
    Seiten:  122 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    Data mining has emerged as a significant technology for gaining knowledge from vast quantities of data. However, concerns are growing that use of this technology can violate individual privacy. These concerns have led to a backlash against the technology, for example, a "Data-Mining Moratorium Act" introduced in the U.S. Senate that would have banned all data-mining programs (including research and development) by the U.S. Department of Defense.

    Privacy Preserving Data Mining provides a comprehensive overview of available approaches, techniques and open problems in privacy preserving data mining. This book demonstrates how these approaches can achieve data mining, while operating within legal and commercial restrictions that forbid release of data. Furthermore, this research crystallizes much of the underlying foundation, and inspires further research in the area.

    Privacy Preserving Data Mining is designed for a professional audience composed of practitioners and researchers in industry. This volume is also suitable for graduate-level students in computer science.

      



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