Abstract
This research presents a new and elaborate security model for IoT devices used in home automation systems. The framework comprises five algorithms: The following models were identified: Vulnerability Assessment (VA), Anomaly Detection with Machine Learning (ADML), Behavior Analysis (BA), Intrusion Detection System (IDS), and Adaptive Security Framework (ASF). Ablation study brings out the specificity of each algorithm and underlines the synergy of the algorithms for IoT device protection. Comparisons with similar procedures confirm higher levels of sensitivity and specificity of the proposed method, as well as enhanced efficiency and tunability. Animated charts give crisp information about the total effects of security methods on different parameters. The proposed security framework has therefore been presented as now a viable solution to complex threats and continuous security for the IoT devices used in home automation systems.
Published Version
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