• DocumentCode
    228881
  • Title

    Somewhat homomorphic cryptography for matrix multiplication using GPU acceleration

  • Author

    Yuan Tian ; Al-Rodhaan, Mznah ; Biao Song ; Al-Dhelaan, Abdullah ; Ting Huai Ma

  • Author_Institution
    Coll. of Comput. & Inf. Sci., King Saud Univ., Riyadh, Saudi Arabia
  • fYear
    2014
  • fDate
    26-27 Aug. 2014
  • Firstpage
    166
  • Lastpage
    170
  • Abstract
    Homomorphic encryption has become a popular research topic since the cloud computing paradigm emerged. This paper discusses the design of a GPU-assisted homomorphic cryptograph for matrix operation. Our proposed scheme is based on an n*n matrix multiplication which are computationally homomorphic. We use more efficient GPU programming scheme with the extension of DGHV homomorphism, which prove the result of verification does not leak any information about the inputs or the output during the encryption and decryption. The performance results are obtained from the executions on a machine equipped with a GeForce GTX 765M GPU. We use three basic parallel algorithms to form efficient solutions which accelerate the speed of encryption and evaluation. Although fully homomorphic encryption is still not practical for real world applications in current stage, this work shows the possibility to improve the performance of homomorphic encryption and achieve this target one step closer.
  • Keywords
    cryptography; graphics processing units; matrix multiplication; parallel algorithms; DGHV homomorphism; GPU acceleration; GPU programming; GeForce GTX 765M GPU; decryption; homomorphic cryptography; matrix multiplication; parallel algorithms; Acceleration; Educational institutions; Encryption; Graphics processing units; Public key; Cloud; Cryptography; GPU; Homomorphic encryption; Matrix multiplication; Privacy; Security;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biometrics and Security Technologies (ISBAST), 2014 International Symposium on
  • Conference_Location
    Kuala Lumpur
  • Print_ISBN
    978-1-4799-6443-7
  • Type

    conf

  • DOI
    10.1109/ISBAST.2014.7013115
  • Filename
    7013115