Privacy Preservation in Distributed Environment Using RSA-CRT View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2016

AUTHORS

Raghvendra Kumar , Prasant Kumar Pattnaik , Yogesh Sharma

ABSTRACT

Most data mining applications are based on information sharing and additional challenges, when we are dealing with data that are containing sensitive or private information. There is no common data mining technique available that deals with private information without any leakage. Therefore, the knowledge extracted from such data may disclose the pattern with sensitive/private information. This may put privacy on the individual/group of parties. In the past few years, privacy preserving data mining has attracted the research interest and potential for a wide area of applications. There are many techniques for privacy preservation like cryptography, anonymity, and randomization, etc., experimented for privacy preservation in data mining. In this paper, information system-based approach is considered, so some of the attributes required higher privacy compared to the other attributes. This paper explores the use of cryptography techniques, namely RSA with Chinese remainder theorem (CRT) to encrypt and decrypt the database, when all the parties are trying to find their global result in presence of trusted third party or absence of trusted third party, without disclosing their private information to each other. More... »

PAGES

29-34

References to SciGraph publications

  • 1994. Number Theory and Cryptography in DURATION AND CHANGE
  • 2004. On Addressing Efficiency Concerns in Privacy-Preserving Mining in DATABASE SYSTEMS FOR ADVANCED APPLICATIONS
  • 1999-04-15. Public-Key Cryptosystems Based on Composite Degree Residuosity Classes in ADVANCES IN CRYPTOLOGY — EUROCRYPT ’99
  • Book

    TITLE

    Proceedings of the Second International Conference on Computer and Communication Technologies

    ISBN

    978-81-322-2516-4
    978-81-322-2517-1

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-81-322-2517-1_4

    DOI

    http://dx.doi.org/10.1007/978-81-322-2517-1_4

    DIMENSIONS

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