Machine Learning-Assisted Secure Channel Establishment for Detecting and Isolating Misdirection Attacks in the Internet of Things
DOI:
https://doi.org/10.54228/mjaret0624002Keywords:
Internet of Things; machine learning; misdirection attacks; secure channel establishment; network securityAbstract
This paper develops a machine-learning assisted approach that works for secure channel establishment in IoT networks. The ultimate goal is to detect and isolate the misdirection threats at network-layer. The proposed system is based on machine learning approach that monitor and analyse the detected attacks from the channel establishment process. That is, it employs a supervised learning. As a result, it can achieve 98.7% detection accuracy with 0.3% false positive rate. In addition, the real-time isolation mechanism can be in place to isolate the detected compromised device within 50 millisecond. The system is designed for different IoT protocols and devices type. The experimental validates that preventive approach can achieve high security and zero trust through our approach to channel establishment in IoT. It is scalable and of minimal impact on performance.
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