Authentication in IoT Networks via Machine Learning and Deep Learning: A Review
Mehwash Weqar, Shabana Mehfuz, Dhawal Gupta · 2024
The area of Internet of Things (IoT) is expanding rapidly and raises numerous issues related to security. In general, IoT devices are resource-constrained, that frequently lead to the attention of cybercriminals. Thus, generating increasingly difficult circumstances in real time. For a reliable IoT system, the threat mitigation tasks are not adequately addressed by the current approaches. The present framework is insufficient to identify the authorized person’s proxy in the connected smart devices. This paper presents an overview of the various threats that can target a particular IoT authentication mechanism at each tier of the architecture. We have analyzed the advancements and inventions made in this discipline. A comparative analysis of the well-known recent ML and DL based authentication techniques, combined with an emphasis on the specific benefits along with drawbacks of every approach has been presented. We have given the suggestions for improving the IoT authentication system for secure communications and offered a strategy for further studies to tackle and overcome these limitations.