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PrivC—A Framework for Efficient Secure Two-Party Computation

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Abstract

Secure Multiparty Computation (SMC) allows mutually distrusted parties to jointly evaluate a function on their private inputs without revealing anything but the output of the function. SMC has been extensively studied for decades by the research community and significant progresses have been made, both in the directions of computing capability and performance improvement. In this work, we design and implement PrivC, an efficient framework for secure two-party computing. Our design was based on arithmetic sharing, oblivious transfer, and garbled circuits. We demonstrate the efficiency of our design and implementation using benchmark datasets and real world applications at our organization. Evaluations have shown that PrivC outperforms several other competitive two-party frameworks.

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Notes

  1. 1.

    We learnt this trick from [25].

  2. 2.

    We provide a classBool to express 1-bit Yao sharing.

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Acknowlegements

We thank Prof. Sheng Zhong, Yuan Zhang, and Jingyu Hua at Nanjing University for their insightful discussions with us on our work. We also thank Dr. Tao Wei, Chief Security Scientist, and Dr. Yueqiang Cheng, Staff Security Scientist at Baidu for their feedbacks and suggestions on our paper.

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Authors and Affiliations

  1. Baidu Inc., Beijing, China

    Kai He, Liu Yang, Jue Hong, Jinghua Jiang, Jieming Wu, Xu Dong & Zhuxun Liang

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  1. Kai He

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  2. Liu Yang

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  3. Jue Hong

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  4. Jinghua Jiang

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  5. Jieming Wu

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  6. Xu Dong

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  7. Zhuxun Liang

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Corresponding author

Correspondence toLiu Yang.

Editor information

Editors and Affiliations

  1. George Mason University, Fairfax, VA, USA

    Songqing Chen

  2. The University of Texas at San Antonio, San Antonio, TX, USA

    Kim-Kwang Raymond Choo

  3. Boston University, Lowell, MA, USA

    Xinwen Fu

  4. Virginia Tech, Blacksburg, VA, USA

    Wenjing Lou

  5. University of Central Florida, Orlando, FL, USA

    Aziz Mohaisen

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© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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He, K.et al. (2019). PrivC—A Framework for Efficient Secure Two-Party Computation. In: Chen, S., Choo, KK., Fu, X., Lou, W., Mohaisen, A. (eds) Security and Privacy in Communication Networks. SecureComm 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 305. Springer, Cham. https://doi.org/10.1007/978-3-030-37231-6_23

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