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Weitersagen:


Herausgeber: 
  • Peeter Laud
  • Liina Kamm
  • Applications of Secure Multiparty Computation 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   i.d.R. innert 7-14 Tagen versandfertig
    Veröffentlichung:  Juli 2015  
    Genre:  EDV / Informatik 
     
    Kryptografie, Verschlüsselungstechnologie
    ISBN:  9781614995319 
    EAN-Code: 
    9781614995319 
    Verlag:  IOS Press 
    Einband:  Gebunden  
    Sprache:  English  
    Dimensionen:  H 240 mm / B 161 mm / D 19 mm 
    Gewicht:  564 gr 
    Seiten:  264 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    We generate and gather a lot of data about ourselves and others, some of it highly confidential. The collection, storage and use of this data is strictly regulated by laws, but restricting the use of data often limits the benefits which could be obtained from its analysis. Secure multi-party computation (SMC), a cryptographic technology, makes it possible to execute specific programs on confidential data while ensuring that no other sensitive information from the data is leaked. SMC has been the subject of academic study for more than 30 years, but first attempts to use it for actual computations in the early 2000s – although theoretically efficient – were initially not practicable. However, improvements in the situation have made possible the secure solving of even relatively large computational tasks. This book describes how many different computational tasks can be solved securely, yet efficiently. It describes how protocols can be combined to larger applications, and how the security-efficiency trade-offs of different components of an SMC application should be chosen. Many of the results described in this book were achieved as part of the project Usable and Efficient Secure Multi-party Computation (UaESMC), which was funded by the European Commission. The book will be of interest to all those whose work involves the secure analysis of confidential data.

      



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