›› 2013, Vol. 28 ›› Issue (1): 152-158.doi: 10.1007/s11390-013-1319-3

• Information Security • Previous Articles     Next Articles

A Secure Scalar Product Protocol Against Malicious Adversaries

Bo Yang1 (杨波), Yong Yu2 (禹勇), and Chung-Huang Yang3 (杨中皇)   

  1. 1. School of Computer Science, Shaanxi Normal University, Xi’an 710062, China;
    2. School of Computer Science and Engineering, University of Electronic Science and Technology of China Chengdu 610054, China;
    3. Graduate Institute of Information and Computer Education, National Kaohsiung Normal University, Taiwan, China
  • Received:2011-10-11 Revised:2012-04-05 Online:2013-01-05 Published:2013-01-05
  • Supported by:

    This work was supported by the National Natural Science Foundation of China under Grant Nos. 60973134, 61173164, 61003232, and the Natural Science Foundation of Guangdong Province of China under Grant No. 10351806001000000.

A secure scalar product protocol is a type of specific secure multi-party computation problem. Using this kind of protocol, two involved parties are able to jointly compute the scalar product of their private vectors, but no party will reveal any information about his/her private vector to another one. The secure scalar product protocol is of great importance in many privacy-preserving applications such as privacy-preserving data mining, privacy-preserving cooperative statistical analysis, and privacy-preserving geometry computation. In this paper, we give an efficient and secure scalar product protocol in the presence of malicious adversaries based on two important tools: the proof of knowledge of a discrete logarithm and the verifiable encryption. The security of the new protocol is proved under the standard simulation-based definitions. Compared with the existing schemes, our scheme offers higher efficiency because of avoiding inefficient cut-and-choose proofs.

[1] Tran D H, Ng W K, Lim H W et al. An efficient cacheable securescalar product protocol for privacy-preserving data mining.In Proc. the 13th Int. Conf. Data Warehousing andKnowledge Discovery, Aug. 29-Sept. 2, 2011, pp.354-366.
[2] Goethals B, Laur S, Lipmaa H, Mielikainen T. On privatescalar product computation for privacy-preserving data mining.In Proc. the 7th Int. Conf. Information Security andCryptology, Dec. 2004, pp.104-120.
[3] Vaidya J, Clifton C. Privacy preserving association rule miningin vertically partitioned data. In Proc. the 8th SIGKDDInt. Conf. Knowledge Discovery and Data Mining, July2002, pp.639-644.
[4] Du W, Atallah M. Privacy-preserving cooperative statisticalanalysis. In Proc. the 17th Annual Computer Security ApplicationsConference, Dec. 2001, pp.102-110.
[5] Atallah M J, Du W. Secure multiparty computational geometry.In Proc. the 7th International Workshop on Algorithmsand Data Structures, Aug. 2011, pp.165-179.
[6] Thomas T. Secure Two-party protocols for point inclusionproblem. Int. J. Network Security, 2009, 9(1): 1-7.
[7] Yang B, Sun A D, Zhang W Z. Secure two-party protocolson planar circles. Journal of Information & ComputationalScience, 2011, 8(1): 29-40.
[8] Yang B, Shao Z Y, Zhang W Z. Secure two-party protocolson planar convex hulls. Journal of Information & ComputationalScience, 2012, 9(4): 915-929.
[9] Du W, Zhan Z. Building decision tree classifier on privatedata. In Proc. IEEE ICDM Workshop on Privacy, Security,and Data Mining, Dec. 2002, Vol.14, pp.1-8.
[10] Amirbekyan A, Estivill-Castro V E C. A new efficient privacypreservingscalar product protocol. In Proc. the 6th AustralasianData Mining Conference, Dec. 2007, pp.209-214.
[11] Hazay C. Efficient two-party computation with simulationbased security [Ph.D. Thesis]. Senate of Bar-Ilan University,Israel, 2009.
[12] Goldreich O. Foundations of Cryptography (Vol.2): Basic Applications.London, UK: Cambridge University Press, 2004.
[13] Schnorr C P. Efficient signature generation by smart cards.Journal of Cryptology, 1991, 4(3): 161-174.
[14] Camenisch J, Shoup V. Practical verifiable encryption anddecryption of discrete logarithms. In Proc. CRYPTO 2003,Aug. 2003, pp.126-144.
[15] Paillier P. Public-key cryptosystems based on composite degreeresidue classes. In Proc. the 17th Theory and Applicationof Cryptographic Techniques, May 1999, pp.223-238.
[16] Jarecki S, Liu X. Efficient oblivious pseudorandom functionwith applications to adaptive OT and secure computation ofset intersection. In Proc. the 6th Theory of CryptographyConference, March 2009, pp.577-594.
No related articles found!
Full text



[1] Chen Fang; Shi Baile;. A Conservative Multiversion Locking-Graph Scheduler Algorithm[J]. , 1991, 6(2): 161 -166 .
[2] Zeng Jianchao; Hidehiko Sanada; Yoshikazu; Tezuka Xu Guangyou;. A Form-Correcting System of Chinese Characters Using a Model of Correcting Procedures of Calligraphists[J]. , 1995, 10(1): 23 -34 .
[3] Zhou Chaochen;. An Overview of Duration Calculus[J]. , 1998, 13(6): 552 .
[4] NIE Xumin; GUO Qing;. Renaming a Set of Non-Horn Clauses[J]. , 2000, 15(5): 409 -415 .
[5] Jian Yu and Cui-Xia Li. Novel Cluster Validity Index for FCM Algorithm[J]. , 2006, 21(1): 137 -140 .
[6] Hao-Jun Ai, Shui-Xian Chen, and Rui-Min Hu. Introduction to AVS Audio[J]. , 2006, 21(3): 360 -365 .
[7] Yu-Bao Liu, Jia-Rong Cai, Jian Yin, and Ada Wai-Chee Fu. Clustering Text Data Streams[J]. , 2008, 23(1): 112 -128 .
[8] Dong-Nian Cheng, Yu-Xiang Hu, and Cai-Xia Liu. Parallel Algorithm Core: A Novel IPSec Algorithm Engine for Both Exploiting Parallelism and Improving Scalability[J]. , 2008, 23(5 ): 792 -805 .
[9] Arianna D'Ulizia, Fernando Ferri, Anna Formica, and Patrizia Grifoni. Approximating Geographical Queries[J]. , 2009, 24(6): 1109 -1124 .
[10] Soon-Gyu Jeong and Sang-Jo Yoo. Distributed Coordinator Election Scheme for QoS Support and Seamless Connectivity in WPANs[J]. , 2009, 24(6): 1138 -1148 .

ISSN 1000-9000(Print)

CN 11-2296/TP

Editorial Board
Author Guidelines
Journal of Computer Science and Technology
Institute of Computing Technology, Chinese Academy of Sciences
P.O. Box 2704, Beijing 100190 P.R. China
E-mail: jcst@ict.ac.cn
  Copyright ©2015 JCST, All Rights Reserved