Analyzing the Vulnerability of Consumer IoT Devices to Sophisticated Phishing Attacks and Ransomware Threats in Home Automation Systems

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.

Authors

Publication Details

Journal
Journal of Intelligent Systems and Internet of Things
Published
2024-12-28
DOI
https://doi.org/10.54216/jisiot.150105
Citations
6
Primary Topic
Advanced Malware Detection Techniques
Type
article
Field-Weighted Citation Impact
2.10
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article

Analyzing the Vulnerability of Consumer IoT Devices to Sophisticated Phishing Attacks and Ransomware Threats in Home Automation Systems

L. L., L. Bhagyalakshmi, Peruri Venkata Anusha, Tejeswar Reddy Velpucharla
6 citations
Journal of Intelligent Systems and Internet of Things
Advanced Malware Detection Techniques
2.10
article

Analyzing the Vulnerability of Consumer IoT Devices to Sophisticated Phishing Attacks and Ransomware Threats in Home Automation Systems

L. L., L. Bhagyalakshmi, Peruri Venkata Anusha, Tejeswar Reddy Velpucharla
article en
6 citations

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.

Journal of Intelligent Systems and Internet of ThingsVol. 15(1)
Openalex Percentile: Top 11%
Advanced Malware Detection Techniques
2.10
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Analyzing the Vulnerability of Consumer IoT Devices to Sophisticated Phishing Attacks and Ransomware Threats in Home Automation Systems — L. L., L. Bhagyalakshmi, et al. · Journal of Intelligent Systems and Internet of Things (2024) | TGRS Research Map | TGRS