MD- \(\mathcal {VC}_{Matrix}\) : An Efficient Scheme for Publicly Verifiable Computation of Outsourced Matrix Multiplication
详细信息    查看全文
  • 关键词:Cloud computing ; Outsourced computation ; Public verification ; Matrix multiplication
  • 刊名:Lecture Notes in Computer Science
  • 出版年:2016
  • 出版时间:2016
  • 年:2016
  • 卷:9955
  • 期:1
  • 页码:349-362
  • 全文大小:380 KB
  • 参考文献:1.Fiore, D., Gennaro, R.: Publicly verifiable delegation of large polynomials and matrix computations, with applications. In: 19th ACM Conference on Computer and Communications Security, pp. 501–512. ACM, New York (2012)
    2.Li, H., Zhang, S., Luan, T.H., Ren, H., Dai, Y., Zhou, L.: Enabling efficient publicly verifiable outsourcing computation for matrix multiplication. In: International Telecommunication Networks and Applications Conference (ITNAC), pp. 44–50. IEEE Press, New York (2015)
    3.Jia, K., Li, H., Liu, D., Yu, S.: Enabling efficient and secure outsourcing of large matrix multiplications. In: IEEE Global Communications Conference (GLOBECOM), pp. 1–6. IEEE Press, New York (2015)
    4.Gennaro, R., Gentry, C., Parno, B.: Non-interactive verifiable computing: outsourcing computation to untrusted workers. In: Rabin, T. (ed.) CRYPTO 2010. LNCS, vol. 6223, pp. 465–482. Springer, Heidelberg (2010). doi:10.​1007/​978-3-642-14623-7_​25 CrossRef
    5.Hu, X., Pei, D., Tang, C., Wong, D.: Verifiable and secure outsourcing of matrix calculation and its application. Scientia inica (Informationis) 43(7), 842–852 (2013)
    6.Chen, X., Huang, X., Li, J., Ma, J., Lou, W., Wong, D.: New algorithms for secure outsourcing of large-scale systems of linear equations. IEEE Trans. Inf. Forensics Secur. 10(1), 69–78 (2015)CrossRef
    7.Caro, D., Iovino, V.: jPBC: java pairing based cryptography. In: IEEE Symposium on Computers and Communications, pp. 850–855. IEEE Press, New York (2011)
    8.Atallah, M., Frikken, K.: Securely outsourcing linear algebra computations. In: 5th ACM Symposium on Information, Computer and Communications Security, pp. 48–59. ACM Press, New York (2010)
    9.Benjamin, D., Atallah, M.J.: Private and cheating-free outsourcing of algebraic computations. In: Sixth Annual Conference on Privacy, Security and Trust (PST 2008), pp. 240–245. IEEE Press, New York (2008)
    10.Mohassel, P.: Efficient and secure delegation of linear algebra. Technical report, Cryptology ePrint Archive, Report 2011/605 (2011)
    11.Lei, X., Liao, X., Huang, T., Li, H., Hu, C.: Outsourcing large matrix inversion computation to a public cloud. IEEE Trans. Cloud Comput. 1(1), 1 (2013). http://​ieeexplore.​ieee.​org/​xpls/​abs_​all.​jsp?​arnumber=​6613485&​tag=​1
    12.Lei, X., Liao, X., Huang, T., Heriniaina, F.: Achieving security, robust cheating resistance, and high-efficiency for outsourcing large matrix multiplication computation to a malicious cloud. Inf. Sci. 280, 205–217 (2014)CrossRef
    13.Lei, X., Liao, X., Huang, T., Li, H.: Cloud computing service: the case of large matrix determinant computation. IEEE Trans. Serv. Comput. 8(5), 688–700 (2015)CrossRef
    14.Wang, C., Ren, K., Wang, J., Wang, Q.: Harnessing the cloud for securely outsourcing large-scale systems of linear equations. IEEE Trans. Parallel Distrib. Syst. 24(6), 1172–1181 (2013)CrossRef
    15.Chen, F., Xiang, T., Yang, Y.: Privacy-preserving and verifiable protocols for scientific computation outsourcing to the cloud. J. Parallel Distrib. Comput. 74(3), 2141–2151 (2014)CrossRef MATH
    16.Nie, H., Ma, H., Wang, J., Chen, X.: Verifiable algorithm for secure outsourcing of systems of linear equations in the case of no solution. In: Ninth International Conference on Broadband and Wireless Computing, Communication and Applications, pp. 572–577. IEEE Press, New York (2014)
    17.Salinas, S., Luo, C., Chen, X., Li, P.: Efficient secure outsourcing of large-scale linear systems of equations. In: IEEE INFOCOM 2015, pp. 1035–1043. IEEE Press, New York (2015)
    18.Murugesan, M., Jiang, W., Clifton, C., Si, L., Vaidya, J.: Efficient privacy-preserving similar document detection. VLDB J. 19(4), 457–475 (2010)CrossRef
    19.Sheng, G., Wen, T., Guo, Q., Yin, Y.: Secure scalar product computation of vectors in cloud computing. J. Northeast. Univ. 34(6), 786–791 (2013)MATH
    20.Backes, M., Fiore, D., Reischuk, R.M.: Verifiable delegation of computation on outsourced data. In: 2013 ACM SIGSAC Conference on Computer & Communications Security, pp. 863–874. ACM, New York (2013)
    21.Wang, C., Ren, K., Wang, J.: Secure practical outsourcing of linear programming in cloud computing. In: IEEE INFOCOM 2011, pp. 820–828. IEEE Press, New York (2011)
    22.Xiang, C., Tang, C., Cai, Y., Xu, Q.: Privacy-preserving face recognition with outsourced computation. Soft Comput. 20(9), 3735–3744 (2016)CrossRef
    23.Liu, A., Zhengy, K., Liz, L., Liu, G., Zhao, L., Zhou, X.: Efficient secure similarity computation on encrypted trajectory data. In: IEEE 31st International Conference on Data Engineering, pp. 66–77. IEEE Press, New York (2015)
    24.Jung, T., Mao, X., Li, X.Y., Tang, S.J., Gong, W., Zhang, L.: Privacy-preserving data aggregation without secure channel: multivariate polynomial evaluation. In: IEEE INFOCOM 2013, pp. 2634–2642. IEEE Press, New York (2013)
  • 作者单位:Gang Sheng (17)
    Chunming Tang (17)
    Wei Gao (18)
    Ying Yin (19)

    17. College of Mathematics and Information Science, Guangzhou University, Guangzhou, 510006, China
    18. School of Mathematics and Statistics Science, Ludong University, Yantai, 264025, China
    19. College of Computer Science and Engineering, Northeastern University, Shenyang, 110004, China
  • 丛书名:Network and System Security
  • ISBN:978-3-319-46298-1
  • 刊物类别:Computer Science
  • 刊物主题:Artificial Intelligence and Robotics
    Computer Communication Networks
    Software Engineering
    Data Encryption
    Database Management
    Computation by Abstract Devices
    Algorithm Analysis and Problem Complexity
  • 出版者:Springer Berlin / Heidelberg
  • ISSN:1611-3349
  • 卷排序:9955
文摘
Cloud service provider that is equipped with tremendous resources enables the terminals with constrained resources to perform outsourced query or computation on large scale data. Security challenges are always the research hotspots in the outsourced computation community. In this paper, we investigate the problem of publicly verifiable outsourced matrix multiplication. However, in the state-of-the-art scheme, a large number of computationally expensive operations are adopted to achieve the goal of public verification. Thus, the state-of-the-art scheme works inefficiently actually due to the fact that most of the time is spent on the verification-related computing. To lower the verification-related time cost, we propose an efficient scheme for public verification of outsourced matrix multiplication. The two-dimensional matrix is transformed into a one-dimensional vector, which retains the computing ability and is used as the substitute for subsequent verification-related work. The security analysis demonstrates the security of the proposed outsourcing scheme, and the performance analysis shows the running efficiency of the scheme.

© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号

地址:北京市海淀区学院路29号 邮编:100083

电话:办公室:(+86 10)66554848;文献借阅、咨询服务、科技查新:66554700