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Cryptanalysis of Tran-Pang-Deng Verifiable Homomorphic Encryption

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Information Security and Cryptology – ICISC 2017 (ICISC 2017)

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Abstract

Tran, Pang and Deng (AsiaCCS’16) proposed two verifiable computation schemes on outsourced encrypted data in the cloud computing scenario. One of them enables the delegation of linear functions and the other is constructed for multivariate quadratic polynomials. In the quadratic function case, it was claimed that their scheme is the first to guarantee both confidentiality of input data and authenticity of computations without using fully homomorphic encryption (FHE). In this paper we present a cryptanalysis which shows that their scheme cannot guarantee confidentiality of input data. We start with a technical lemma on pseudorandom functions that have a range of Abelian group and then provides a simple attack which allows the adversary to successfully break the scheme with probability close to 1.

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Acknowledgment

The authors would like to thank the anonymous referees for the helpful comments. The research was supported by NSFC (No. 61602304) and Pujiang Talent Program (No. 16PJ1406500).

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Authors and Affiliations

  1. School of Information Science and Technology, ShanghaiTech University, Shanghai, 201210, People’s Republic of China

    Shuaijianni Xu, Yan He & Liang Feng Zhang

  2. Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, 200050, People’s Republic of China

    Shuaijianni Xu & Yan He

Authors
  1. Shuaijianni Xu
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  2. Yan He
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Correspondence to Liang Feng Zhang .

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Editors and Affiliations

  1. Pusan National University, Busan, Korea (Republic of)

    Howon Kim

  2. Kookmin University, Seoul, Korea (Republic of)

    Dong-Chan Kim

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Xu, S., He, Y., Zhang, L.F. (2018). Cryptanalysis of Tran-Pang-Deng Verifiable Homomorphic Encryption. In: Kim, H., Kim, DC. (eds) Information Security and Cryptology – ICISC 2017. ICISC 2017. Lecture Notes in Computer Science(), vol 10779. Springer, Cham. https://doi.org/10.1007/978-3-319-78556-1_4

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  • DOI: https://doi.org/10.1007/978-3-319-78556-1_4

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  • Online ISBN: 978-3-319-78556-1

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