提出了一种名为 MLQENABLER 的新方案，旨在实现云计算环境中对加密数据库的安全机器学习查询。该方法通过允许客户在将数据外包给公共云服务提供商之前对其进行加密，从而解决了使用公共云服务提供商带来的安全问题。MLQENABLER 利用一种辅助索引的方法来同时保持安全性和机器学习能力，初步实验表明其安全级别可接受，且性能下降轻微。 AI
影响 增强了利用云端加密数据的机器学习应用程序的安全性。
排序理由 该集群描述了一篇研究论文，其中详细介绍了一种用于加密数据库安全机器学习查询的新方案。
AI 生成摘要 · Google Gemini · 来自 3 个来源。 我们如何撰写摘要 →
arXiv:2607.08197v1 Announce Type: cross Abstract: In cloud computing, the public cloud service providers (CSPs) can provide cloud storage as the primary service while providing additional machine learning (ML)-based services by using the clients' data in storage. This business mo…
In cloud computing, the public cloud service providers (CSPs) can provide cloud storage as the primary service while providing additional machine learning (ML)-based services by using the clients' data in storage. This business model extends the border of cloud computing services…
In cloud computing, the public cloud service providers (CSPs) can provide cloud storage as the primary service while providing additional machine learning (ML)-based services by using the clients' data in storage. This business model extends the border of cloud computing services…