| 연구 내용 소개 | |
| Private AI 및 이를 위한 Privacy Preserving Computation 에 대한 연구를 진행하고 있습니다. |
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Privacy-Preserving Deep Sequential Model with Matrix Homomorphic Encryption (ASIACCS, 2022.) |
| Making deep neural networks available as a service introduces privacy problems, for which homomorphic encryption of both model and user data potentially offers the best solution. However, the difficulty of operating on homomorphically encrypted data has hither to limited the range of operations available and the depth of networks. We introduce an extended CKKS scheme MatHEAAN to provide efficient matrix representations and operations together with improved noise control. Using the MatHEAAN we developed a deep sequential model with a gated recurrent unit called MatHE-GRU. We evaluated the proposed model using sequence modeling, regression, and classification of images and genome sequences. We show that the hidden states of the encrypted model, as well as the results, are consistent with a plaintext model. | |
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Privacy-Preserving Deep Sequential Model with Matrix Homomorphic Encryption (ASIACCS, 2022.) |
| Making deep neural networks available as a service introduces privacy problems, for which homomorphic encryption of both model and user data potentially offers the best solution. However, the difficulty of operating on homomorphically encrypted data has hither to limited the range of operations available and the depth of networks. We introduce an extended CKKS scheme MatHEAAN to provide efficient matrix representations and operations together with improved noise control. Using the MatHEAAN we developed a deep sequential model with a gated recurrent unit called MatHE-GRU. We evaluated the proposed model using sequence modeling, regression, and classification of images and genome sequences. We show that the hidden states of the encrypted model, as well as the results, are consistent with a plaintext model. | |
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Efficient Sorting of Homomorphic Encrypted Data with k-Way Sorting Network (IEEE Transactions on Information Forensics and Security, 2021.) |
| We have found an efficient sorting method over encrypted data by applying k-way sorting network to the encrypted data by CKKS. With the help of efficient data comparison method and SIMD operations supported by CKKS HE, we could sort tens of thousands of data very quickly. | |
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Over 100x Faster Bootstrapping in Fully Homomorphic Encryption through Memory-centric Optimization with GPUs. (In Proc. CHES 21, 2021.) |
| We have demonstrated that very fast CKKS HE operations are possible including the bootrapping operation with the help of GPU. We also have figured out the importance of the memory bandwitdh for efficient HE operations. | |
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| 참고 | 정보보호 분야 Top journal list |
| 정보보호 분야 Top conference & Journal list |
