• DocumentCode
    2919211
  • Title

    Using Homomorphic Encryption and Digital Envelope Techniques for Privacy Preserving Collaborative Sequential Pattern Mining

  • Author

    Zhan, Justin

  • Author_Institution
    Carnegie Mellon Univ., Pittsburgh
  • fYear
    2007
  • fDate
    23-24 May 2007
  • Firstpage
    331
  • Lastpage
    334
  • Abstract
    Nowadays, data mining is widely used in various applications. Privacy is an important issue in data mining systems. By privacy, we mean how to conduct data mining without compromising much data privacy. In particular, we consider the scenario where data sharing for data mining purpose is the main goal. However, we would like minimize the data disclosure during data mining process.
  • Keywords
    cryptography; data mining; data privacy; data mining; digital envelope techniques; homomorphic encryption; privacy preserving collaborative sequential pattern mining; Collaboration; Cryptography; Data mining; Data privacy; Databases; Explosions; Internet; Protocols;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligence and Security Informatics, 2007 IEEE
  • Conference_Location
    New Brunswick, NJ
  • Electronic_ISBN
    1-4244-1329-X
  • Type

    conf

  • DOI
    10.1109/ISI.2007.379493
  • Filename
    4258719