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Secure Evaluation of Discrete Sine Transform in Homomorphic Encrypted Domain

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Artificial Intelligence and Security (ICAIS 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13339))

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Abstract

Discrete sine transform (DST) is widely used in compression encoding, image processing, and speech enhancement. In cloud computing, outsourcing plaintext data to the cloud has the risk of private data leakage. In this paper, we study how to realize data computation outsourcing with privacy protection. We propose a scheme to implement DST in the encrypted domain that uses the scaling method to represent decimals. To improve the accuracy, we also propose a new scheme to implement high precision encrypted domain DST. We approximate complex numbers with high precision using integer coefficient polynomials whose independent variable is a unit root. With this representation, we can perform DST in the encryption domain with high precision. We conducted experiments to verify the effectiveness and efficiency. The two schemes have the advantages of high speed and high precision, respectively.

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Acknowledgements

This work was supported in part by the Natural Science Foundation of Guangdong (2019A1515010746, 2022A1515011897), in part by the Science and Technology Projects in Guangzhou (202102080354), in part by the Open Foundation of Henan Key Laboratory of Cyberspace Situation Awareness (HNTS2022023).

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Authors and Affiliations

  1. School of Computer Science and Engineering Guangdong Key Laboratory of Information Security Technology, Sun Yat-sen University, Guangzhou, 510006, China

    Huicong Zeng, Zhiwei Cai, Peijia Zheng, Hongmei Liu & Weiqin Luo

  2. State Key Laboratory of Information Security, Institute of Information Engineering, Chinese Academy of Sciences, Beijing, 100093, China

    Peijia Zheng

Authors
  1. Huicong Zeng
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  2. Zhiwei Cai
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  3. Peijia Zheng
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  4. Hongmei Liu
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  5. Weiqin Luo
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Corresponding authors

Correspondence to Peijia Zheng or Hongmei Liu .

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Editors and Affiliations

  1. Nanjing University of Information Science and Technology, Nanjing, China

    Xingming Sun

  2. Nanjing University of Information Science and Technology, Nanjing, China

    Xiaorui Zhang

  3. Jinan University, Guangzhou, China

    Zhihua Xia

  4. Purdue University, West Lafayette, IN, USA

    Elisa Bertino

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Zeng, H., Cai, Z., Zheng, P., Liu, H., Luo, W. (2022). Secure Evaluation of Discrete Sine Transform in Homomorphic Encrypted Domain. In: Sun, X., Zhang, X., Xia, Z., Bertino, E. (eds) Artificial Intelligence and Security. ICAIS 2022. Lecture Notes in Computer Science, vol 13339. Springer, Cham. https://doi.org/10.1007/978-3-031-06788-4_43

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  • DOI: https://doi.org/10.1007/978-3-031-06788-4_43

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  • Online ISBN: 978-3-031-06788-4

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