English(EN) Pacifo: An Efficient Fully Homomorphic Encryption-based Lightweight ResNet for Trustworthy Machine Learning as a Service

Pacifo框架增强机器学习推理的隐私性

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-27 04:00

研究人员开发了Pacifo，一个利用全同态加密（FHE）来增强机器学习推理服务隐私性和效率的框架。Pacifo通过分割层和近似ReLU函数来适配ResNet20模型，显著降低了FHE操作相关的计算开销和延迟。与现有ResNet20的FHE实现相比，该方法实现了3.7-21.7倍的速度提升，同时保持了原始模型95%-99%的准确率。 AI

影响提高了机器学习推理服务的隐私性和效率，可能支持更安全的AI应用部署。

排序理由该集群包含一篇学术论文，详细介绍了一种用于机器学习推理的新框架和模型适配。 [lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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报道来源 [1]

arXiv cs.AI TIER_1 English(EN) · Yang Li, Gang He, Ruichen Zhang, Guangyuan Liu, Yinqiu Liu · 2026-10-27 04:00

Pacifo：一种基于全同态加密的高效轻量级ResNet，用于可信的机器学习即服务

arXiv:2610.33525v1 Announce Type: cross Abstract: Machine Learning as a Service (MLaaS) has become a popular paradigm for deploying AI applications. However, it raises significant privacy concerns that the raw client data needs to be uploaded to the server for inference services.…

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报道来源 [1]

Pacifo：一种基于全同态加密的高效轻量级ResNet，用于可信的机器学习即服务

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