Gorabal, Jayanna Veeranna
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Core machine learning methods for boosting security strength for securing IoT Pavithran, Sneha Nelliyadan; Gorabal, Jayanna Veeranna
Indonesian Journal of Electrical Engineering and Computer Science Vol 39, No 3: September 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v39.i3.pp1891-1899

Abstract

Internet-of-things (IoT) revolutionized the mechanism of larger scale of network system offering more engaged, automated, and resilient data dissemination process. However, the resource-limited IoT devices potentially suffers from security issues owing to various inherent weakness. Artificial intelligence (AI) and machine learning (ML) has evolved more recently towards boosting up the security features of IoT offering a secure environment with higher privacy. Till date, there are various review papers to discuss elaborately security aspect of an IoT; however, they miss out to present the actual gap existing between commercial available products and research-based models. Hence, this paper contributes towards discussing the core taxonomy of evolving security methods using ML along with their research trend to offer better insight to existing state of effectiveness. The study further contributes towards highlighting the potential trade-off between the real-world solution and on-going ML based approaches.