• DocumentCode
    3322741
  • Title

    Efficient Data Authentication in an Environment of Untrusted Third-Party Distributors

  • Author

    Atallah, Mikhail J. ; Cho, YounSun ; Kundu, Ashish

  • Author_Institution
    Dept. of Comput. Sci., Purdue Univ. West Lafayette, West Lafayette, IN
  • fYear
    2008
  • fDate
    7-12 April 2008
  • Firstpage
    696
  • Lastpage
    704
  • Abstract
    In the third-party model for the distribution of data, the trusted data creator or owner provides an untrusted party V with data and integrity verification (IV) items for that data. When a user U gets a subset of the data at D or is already in possession of that subset, U may request from D the IV items that make it possible for U to verify the integrity of its data: D must then provide U with the (hopefully small) number of needed IVs. Most of the published work in this area uses the Merkle tree or variants thereof. For the problem of 2-dimensional range data, the best published solutions require V to store O(n log n) IV items for a database of n items, and allow a user IA to be sent only O(log n) of those IVs for the purpose of verifying the integrity of the data it receives from D (regardless of the size of lA´s query rectangle). For data that is modeled as a 2-dimensional grid (such as GIS or image data), this paper shows that better bounds are possible: The number of IVs stored at D (and the time it takes to compute them) can be brought down to O(n), and the number of IVs sent to IA for verification can be brought down to a constant.
  • Keywords
    authorisation; data integrity; database management systems; Merkle tree; data authentication; data distribution; data integrity; data verification; database; integrity verification; untrusted party V; untrusted third-party distributors; Authentication; Computer science; Cryptography; Data security; Databases; Digital signatures; Geographic Information Systems; Government; Grid computing; Subscriptions;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data Engineering, 2008. ICDE 2008. IEEE 24th International Conference on
  • Conference_Location
    Cancun
  • Print_ISBN
    978-1-4244-1836-7
  • Electronic_ISBN
    978-1-4244-1837-4
  • Type

    conf

  • DOI
    10.1109/ICDE.2008.4497478
  • Filename
    4497478