An asterisk (*) implies corresponding author.

International Conferences

1. Dongjin Park, Eunsang Lee*, Joon-Woo Lee*, "Powerformer: Efficient and High-Accuracy Privacy-Preserving Language Model with Homomorphic Encryption." In Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (ACL 2025), pp. 11090–11111, Vienna, Austria. Association for Computational Linguistics, 2025. (Top-tier natural language processing conference)

2. Joon-Woo Lee, Eunsang Lee*, Young-Sik Kim*, Jong-Seon No, "Rotation Key Reduction for Client-Server Systems of Deep Neural Network on Fully Homomorphic Encryption." In Annual International Conference on the Theory and Applications of Cryptology and Information Security (ASIACRYPT 2023), pp. 36-68, Springer, 2023. (Top-tier cryptography conference)

3. Eunsang Lee, Joon-Woo Lee*, Junghyun Lee, Young-Sik Kim, Yongjune Kim, Jong-Seon No, and Woosuk Choi, "Low Complexity Deep Convolutional Neural Networks on Fully Homomorphic Encryption Using Multiplexed Parallel Convolutions." In International Conference on Machine Learning (ICML 2022), pp. 12403-12422, PMLR, 2022. (Top-tier machine learning conference)

4. Joon-Woo Lee*, Eunsang Lee, Yongwoo Lee, Young-Sik Kim, and Jong-Seon No, "High-Precision Bootstrapping of RNS-CKKS Homomorphic Encryption Using Optimal Minimax Polynomial Approximation and Inverse Sine Function." In Annual International Conference on the Theory and Applications of Cryptographic Techniques (EUROCRYPT 2021), pp. 618-647, Springer, 2021. (Top-tier cryptography conference)

International Journals

1. Junghyun Lee, Eunsang Lee*, Joon-Woo Lee*, Yongjune Kim, Young-Sik Kim, and Jong-Seon No, "Precise Approximation of Convolutional Neural Networks for Homomorphically Encrypted Data." IEEE Access, 11:62062-62076, 2023.

2. Eunsang Lee, Joon-Woo Lee, Young-Sik Kim*, and Jong-Seon No, "Optimization of Homomorphic Comparison Algorithm on RNS-CKKS Scheme." IEEE Access, 10:26163-26176, 2022.

3. Joon-Woo Lee, Hyungchul Kang, Yongwoo Lee, Woosuk Choi, Jieun Eom, Maxim Deryabin, Eunsang Lee, Junghyun Lee, Donghoon Yoo, Young-Sik Kim*, and Jong-Seon No, "Privacy-Preserving Machine Learning with Fully Homomorphic Encryption for Deep Neural Network." IEEE Access, 10:30039-30054, 2022.

4. Eunsang Lee, Joon-Woo Lee*, Jong-Seon No, and Young-Sik Kim, "Minimax Approximation of Sign Function by Composite Polynomial for Homomorphic Comparison." IEEE Transactions on Dependable and Secure Computing, 19(6):3711-3727, 2021 (IF: 7.329, Top 2.31%).

5. Minki Song, Seunghwan Lee, Dong-Joon Shin*, Eunsang Lee, Young-Sik Kim, and Jong-Seon No, "Analysis of Error Dependencies on Newhope." IEEE Access, 8:45443-45456, 2020.

6. Eunsang Lee, Young-Sik Kim*, Jong-Seon No, Minki Song, and Dong-Joon Shin, "Modication of FrodoKEM Using Gray and Error-Correcting Codes." IEEE Access, 7:179564-179574, 2019.

Domestic Journal

1. Soomin Park and Eunsang Lee*. Accelerating ResNet Inference on RNS-CKKS with Merged Bootstrapping. The Journal of Korean Institute of Communications and Information Sciences, 50(11):1669-1678, 2025.

2. Yamada Akihiko and Eunsang Lee*, "Analysis of Research Trends in Homomorphic Encryption Using Bibliometric Analysis." Journal of Korea Institute of Information Security and Cryptology, 33(4):601-608, 2023.

3. Eunsang Lee*, "Precise Max-Pooling on Fully Homomorphic Encryption." Journal of Korea Institute of Information Security and Cryptology, 33(3):375-381, 2023.

4. Eunsang Lee* and Jong-Seon No, "Method for Improving the 256-Bit Cryptosystem FrodoKEM Using Gray and Error-Correcting Codes." Journal of Korean Institute of Communications and Information Sciences, 45(6):998-1003, 2020.