新的VERITAS协议增强了图学习中的隐私和安全性

作者 PulseAugur 编辑部 · [1 个来源] · 2026-09-10 04:00

研究人员推出了一种名为VERITAS的新协议，旨在增强图学习系统的安全性和隐私性。VERITAS通过实施一种“信任但验证”机制，解决了本地私有图学习协议易受数据投毒攻击的漏洞。该协议对用户数据进行本地扰动，然后使用双边认证来识别和移除恶意节点，最终恢复效用并确保稳健的私有图学习。 AI

影响增强了去中心化图学习应用的安全性与隐私性。

排序理由这是一篇详细介绍图学习新协议的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

AI 生成摘要 · Google Gemini · 来自 1 个来源。我们如何撰写摘要 →

本文如何被排名

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arXiv cs.LG TIER_1 English(EN) · Longzhu He, Li Sun, Hao Peng, Ruijie Wang, Raymond Chi-Wing Wong, Sen Su · 2026-09-10 04:00

信任但需验证：抗投毒的本地化隐私图学习协议

arXiv:2609.07063v1 Announce Type: new Abstract: Built upon local differential privacy (LDP), locally private graph learning protocols have emerged as an important paradigm for decentralized graph learning, balancing privacy protection and learning utility. Under such protocols, e…