Fast Authentication and Progressive Authorization in Large-Scale IoT: How to Leverage AI for Security Enhancement?

作者: He Fang , Angie Qi , Xianbin Wang

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摘要: Security provisioning has become the most important design consideration for large-scale Internet of Things (IoT) systems due to their critical roles support diverse vertical applications by connecting heterogenous devices, machines and industry processes. Conventional authentication authorization schemes are insufficient in dealing emerging IoT security challenges reliance on both static digital mechanisms computational complexity improving level. Furthermore, isolated designs different layers link segments while ignoring overall protection lead cascaded risks as well growing communication latency overhead. In this article, we envision new artificial intelligence (AI) enabled approaches overcome these issues achieving fast progressive authorization. To be more specific, a lightweight intelligent approach is developed exploring machine learning at gateway identify access time slots or frequencies resource-constraint devices. Then propose holistic approach, where online trust management adopted analyzing complex dynamic environment adaptive control. These AI establish connections between transceivers quickly enhance progressively, so that can reduced well-controlled IoT. Finally, outline several areas AI-enabled future researches.

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