Privacy Preserving Inner Product of Vectors in Cloud Computing
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Ying Yin | Tao Wen | Quan Guo | Gang Sheng
[1] Gu Si-yang,et al. Privacy preserving association rule mining in vertically partitioned data , 2006 .
[2] Artak Amirbekyan,et al. A New Efficient Privacy-Preserving Scalar Product Protocol , 2007, AusDM.
[3] Yin Ying. Secure Scalar Product Computation of Vectors in Cloud Computing , 2013 .
[4] Mark Ryan,et al. Cloud computing security: The scientific challenge, and a survey of solutions , 2013, J. Syst. Softw..
[5] Ying Yin,et al. Verifying correctness of inner product of vectors in cloud computing , 2013, Cloud Computing '13.
[6] Pascal Paillier,et al. Public-Key Cryptosystems Based on Composite Degree Residuosity Classes , 1999, EUROCRYPT.
[7] Huang Liusheng,et al. Privacy Protection in the Relative Position Determination for Two Spatial Geometric Objects , 2006 .
[8] Yong Yu,et al. A Secure Scalar Product Protocol Against Malicious Adversaries , 2013, Journal of Computer Science and Technology.
[9] Chris Clifton,et al. Efficient privacy-preserving similar document detection , 2010, The VLDB Journal.
[10] Bart Goethals,et al. On Private Scalar Product Computation for Privacy-Preserving Data Mining , 2004, ICISC.
[11] Wenliang Du,et al. Privacy-preserving cooperative statistical analysis , 2001, Seventeenth Annual Computer Security Applications Conference.
[12] Liusheng Huang,et al. A protocol for the secure two-party quantum scalar product , 2012 .