2025年4月18日-20日，第三届信息通信及安全数学理论年会暨信息通信及安全数学理论专业委员会第一届第四次全体会议在北京四季御园国际大酒店成功召开。本次会议由中国通信学会信息通信及安全数学理论专业委员会主办，中国科学院大学密码学院承办，并得到华为技术有限公司的大力支持。
国科大密码学院院长荆继武教授受邀出席开幕式并致辞。他代表学院全体师生对与会专家学者表示热烈欢迎，同时向与会专家介绍了密码学院的发展历程。
国科大密码学院荆继武院长致辞
会议聚焦通信理论及信息安全相关数学理论，邀请了陈立教授、李念教授、宁建廷教授、金玲飞教授、魏恒嘉教授、袁晨教授、孙黎副教授、王晗副研究员、李康荃副教授、陈师尧老师共10位知名专家作学术报告。会议吸引了50余位资深专家和青年学者参与，为信息通信及安全数学理论领域的学术交流与合作提供了重要平台。
参会人员合影
2025年5月，国科大密码学院郑昉昱副教授在IEEE Transactions on Parallel and Distributed Systems (TPDS)期刊发表了题为“GIF-FHE: A Comprehensive Implementation and Evaluation of GPU-accelerated FHE with Integer and Floating-point Computing Power”的研究论文。论文中提出了一种基于GPU浮点数和定点数混合的全同态加密算法实现。该研究工作得到国家密码科学基金（2025NCSF02005）的支持。
Abstract：Fully Homomorphic Encryption (FHE) allows computations on encrypted data without revealing the plaintext, garnering significant interest from both academic and industrial communities. However, its broader adoption has been hindered by performance limitations. Consequently, researchers have turned to GPUs for efficient FHE implementation. Nevertheless, most have predominantly favored integer units due to their ease of use, overlooking the considerable computational potential of floating-point units in GPUs.
Recognizing this untapped floating-point computational power, our paper introduces GIF-FHE, an extensive exploration and implementation of FHE, leveraging GPUs' integer and floating-point instructions for FHE acceleration. We develop a comprehensive suite of low-level and middle-level FHE primitives, offering multiple implementation variants with support for three word size configurations (64/52/32-bit). Particularly, we make innovative use of floating-point implementations, employing a novel methodology to efficiently leverage the floating-point unit's fused multiply-add (FMA) instructions. This represents the pioneering integration of floating-point units into FHE acceleration. To bridge our highly-optimized FHE primitives with practical applications, this paper also provides a high-level FHE implementation and interfaces that can be directly applied by upper-level applications such as neural network inference. Finally, we undertake a comprehensive experiment evaluation and comparison involving three types of arithmetic: FP64/INT64/INT32 with varying word size configurations and computation units. Notably, our fundamental function implementations consistently outperform counterparts on the same platform, achieving speedups ranging from 2.0× to 4.2×. In the context of CKKS FHE schemes, our homomorphic operation implementation surpasses the state-of-the-art GPU-based solution with a speedup of up to 3.8×, and exceeds the performance of the widely adopted CPU-based library, SEAL, with a remarkable speedup of over 300×.
论文信息：Fangyu Zheng, Guang Fan, Wenxu Tang, Yixuan Song, Tian Zhou, Yuan Zhao, Jiankuo Dong, Jingqiang Lin, Shoumeng Yan, Jiwu Jing, “GIF-FHE: A Comprehensive Implementation and Evaluation of GPU-accelerated FHE with Integer and Floating-point Computing Power”, IEEE Transactions on Parallel and Distributed Systems (TPDS), 2025, doi: 10.1109/TPDS.2025.3574481.（CCF-A）
(原文链接：https://www.computer.org/csdl/journal/td/5555/01/11016794/275gzaDiIko)
3月7日，国科大密码学院在玉泉路校区组织召开了2025年密码学院规划工作会。会议由学院名誉院长冯登国院士主持，学院学术委员会专家及全体教师参加了此次会议。
会议的主要议程包括听取学院院长、管理支撑岗、教学科研岗及科研助理等全体教职员工关于2025年的工作计划汇报，并审阅了相关材料。学术委员会专家从多个方面对学院的未来发展提出了宝贵的意见和建议，涵盖学院班子建设、人员构成、教学体系、学院整体规划、年度重点工作以及科研方向等。
通过专家们的指导和建议，学院将进一步优化人员结构，完善教学体系，明确科研方向，确保各项任务落到实处，推动学院在密码学研究和人才培养方面取得更大的成就。
会议现场照片
