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Rotation Key Reduction for Client-Server Systems of Deep Neural Network on Fully Homomorphic Encryption

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Advances in Cryptology – ASIACRYPT 2023 (ASIACRYPT 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14443))

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Abstract

In this paper, we propose a new concept of hierarchical rotation key for homomorphic encryption to reduce the burdens of the clients and the server running on the fully homomorphic encryption schemes such as Cheon-Kim-Kim-Song (CKKS) and Brakerski/Fan-Vercauteran (BFV) schemes. Using this concept, after the client generates and transmits only a small set of rotation keys to the server, the server can generate any required rotation keys from the public key and the smaller set of rotation keys that the client sent. This proposed method significantly reduces the communication cost of the client and the server, and the computation cost of the client. For example, if we implement the standard ResNet-18 network for the ImageNet dataset with the CKKS scheme, the server requires 617 rotation keys. It takes 145.1 s for the client with a personal computer to generate whole rotation keys and the total size is 115.7 GB. If we use the proposed two-level hierarchical rotation key system, the size of the rotation key set generated and transmitted by the client can be reduced from 115.7 GB to 2.91 GB (\(\times \)1/39.8), and the client-side rotation key generation runtime is reduced from 145.1 s to 3.74 s (\(\times \)38.8 faster) without any changes in any homomorphic operations to the ciphertexts. If we use the three-level hierarchical rotation key system, the size of the rotation key set generated and transmitted by the client can be further reduced from 1.54 GB (\(\times \)1/75.1), and the client-side rotation key generation runtime is further reduced to 1.93 s (\(\times \)75.2 faster) with a slight increase in the key-switching operation to the ciphertexts and further computation in the offline phase.

E. Lee and Y.-S. Kim—Co-corresponding authors.

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Notes

  1. 1.

    The full version of the paper [27] includes the preliminaries, the proofs of the theorems, and the required cyclic shifts for ResNet models.

  2. 2.

    The proof can be found in the full version of the paper [27].

  3. 3.

    The proof can be found in the full version of the paper [27].

  4. 4.

    The specific rotation steps can be found in the full version of this paper [27].

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Acknowledgements

This work was supported in part by the Institute of Information and Communications Technology Planning and Evaluation (IITP) grant funded by the Korea Government [Ministry of Science and ICT (MSIT)]), Development of Highly Efficient Post-Quantum Cryptography (PQC) Security and Performance Verification for Constrained Devices under Grant 2021-0-00400, and in part by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (No. 2022R1I1A1A01-06828412), and in part the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. NRF-2021R1A2C2011082).

We would like to express our gratitude to the anonymous reviewers who provided insightful suggestions for effective experiments highlighting the utility of the techniques in this paper.

Author information

Authors and Affiliations

  1. School of Computer Science and Engineering, Chung-Ang University, Seoul, Republic of Korea

    Joon-Woo Lee

  2. Department of Software, Sejong University, Seoul, Republic of Korea

    Eunsang Lee

  3. Department of Electrical Engineering and Computer Science, DGIST, Daegu, Republic of Korea

    Young-Sik Kim

  4. Department of Electrical and Computer Engineering, INMC, Seoul National University, Seoul, Republic of Korea

    Jong-Seon No

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Correspondence to Eunsang Lee or Young-Sik Kim .

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Editors and Affiliations

  1. Nanyang Technological University, Singapore, Singapore

    Jian Guo

  2. Monash University, Melbourne, VIC, Australia

    Ron Steinfeld

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Lee, JW., Lee, E., Kim, YS., No, JS. (2023). Rotation Key Reduction for Client-Server Systems of Deep Neural Network on Fully Homomorphic Encryption. In: Guo, J., Steinfeld, R. (eds) Advances in Cryptology – ASIACRYPT 2023. ASIACRYPT 2023. Lecture Notes in Computer Science, vol 14443. Springer, Singapore. https://doi.org/10.1007/978-981-99-8736-8_2

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  • DOI: https://doi.org/10.1007/978-981-99-8736-8_2

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