| 发表状态 | 已发表Published |
| 题名 | VESTA: A Secure and Efficient FHE-based Three-Party Vectorized Evaluation System for Tree Aggregation Models |
| 作者 | |
| 发表日期 | 2025-06-09 |
| 会议名称 | 51st ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems |
| 来源出版物 | SIGMETRICS Abstracts 2025 - Abstracts of the 2025 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems |
| 页码 | 31-33 |
| 会议日期 | 9 June 2025 - 13 June 2025 |
| 会议地点 | Stony Brook |
| 摘要 | Machine Learning as a Service (MLaaS) platforms facilitate collaborative machine learning, but trust issues necessitate privacy-preserving methods. As for tree ensembles, prior Fully Homomorphic Encryption (FHE)-based approaches suffer from slow inference speed and high memory usage. This work proposes the VESTA system that leverages compile-time precomputation and parallelizable model partitioning to enhance performance. VESTA achieves a 2.1x speedup and reduces memory consumption by 59.4% compared to state-of-the-art solutions. |
| 关键词 | domain-specific compiler homomorphic encryption parallelism tree ensembles vectorization |
| DOI | 10.1145/3726854.3727331 |
| 相关网址 | 查看来源 |
| 语种 | 英语English |
| Scopus入藏号 | 2-s2.0-105010303357 |
| 引用统计 | |
| 文献类型 | 会议摘要&总结 |
| 条目标识符 | https://repository.uic.edu.cn/handle/39GCC9TT/13258 |
| 专题 | 理工科技学院 |
| 通讯作者 | Liu, Hongyuan |
| 作者单位 | 1.The Hong Kong University of Science and Technology (Guangzhou),Guangzhou,Guangdong,China 2.Guangdong Provincial/Zhuhai Key Laboratory of Irads,BNU-HKBU United International College,Zhuhai,Guangdong,China 3.Hong Kong Baptist University,Hong Kong,Hong Kong 4.School of Cyber Science and Technology,Shandong University,Qingdao,Shandong,China |
| 推荐引用方式 GB/T 7714 | Zhao, Haosong,Huang, Junhao,Chen, Zihanget al. VESTA: A Secure and Efficient FHE-based Three-Party Vectorized Evaluation System for Tree Aggregation Models. 2025. |
| 条目包含的文件 | 条目无相关文件。 | |||||
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