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English(EN) An AI-Based Solution for Secure Service Provisioning in IoT

AI框架利用DRL和FL增强物联网安全性

研究人员开发了一个新颖的AI框架,通过智能选择合适的智能对象进行服务供应来增强物联网(IoT)的安全性。该系统利用深度强化学习(DRL)在安全约束下进行自适应服务选择,并利用联邦学习(FL)进行分布式行为监控。这种方法计算服务提供商的可靠性得分,确保选择同时考虑功能适用性和对安全协议的遵守情况,实验结果表明即使在资源受限的IoT设备上也能有效。 AI

影响 这项研究为现代物联网生态系统提供了一种可扩展的安全机制,有望提高连接设备的可靠性和安全性。

排序理由 学术论文,详细介绍了一种针对特定技术问题的新的基于AI的解决方案。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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

AI框架利用DRL和FL增强物联网安全性

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学术论文,详细介绍了一种针对特定技术问题的新的基于AI的解决方案。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Marco Arazzi, Mert Cihangiroglu, Serena Nicolazzo, Antonino Nocera, Vinod P ·

    一种基于人工智能的安全物联网服务供应解决方案

    arXiv:2606.30701v1 Announce Type: cross Abstract: As the Internet of Things (IoT) continues its rapid expansion, the attack surface grows accordingly, with emerging threats targeting smart objects and their interactions. In this evolving landscape, securing service provisioning i…