Secure IoT: Fortifying IoT Security with Support Vector Machines

The Secure IoT will be a proposed system aim for bolstering the security of Internet supported things (IoT) networks by the innovative application of Supportive Vector Machines (SVMs). As the proliferation of IoT Modules will continues to expand for ensuring the integrity and confidentiality of data packets transmitted within these networks may become paramount. In Traditional security will measures often fall short on detecting sophisticated cyber external-attacks targeting the IoT infrastructures. Secure IoT will addresses this challenging of by harnessing the power of SVMs, a powerful machine Learning-Driven technique, to effective in identify and mitigate potential intrusions. The proposed system may operate by analyzing the vast amounts of data packets generated by IoT Modules by including network traffic patterns, device behavioral activities, and communication protocols. SVMs are will employed to classifying of this data packets into distinct categories, by distinguishing between normal activities and suspicious anomalies indicatives of security breaches. By leveraging SVMs' capability to find optimal hyper planes that separate different classes of data packets, Secure IoT could accurately detect and responding to malicious activities in practical. The Key feature of Secure IoT will include robust anomaly detection capabilities and adaptability to dynamic IoT environments, and scalability to accommodate large-scale IoT deployments. Moreover, the utilization of SVMs will enables the system to handles high-dimensional data packets with efficiency and accuracy in making it suitable for diverse IoT applications across various industries. In proposal, Secure IoT represents a significant advancement in IoT security, by offering a proactive and intelligent defense mechanism against emerging Cyber external-attacks. By leverages Supportive Vector Machines methodology, this proposed system might provide a Comprehensively solution for safeguarding the IoT networks and preserving of the confidentiality, integrity, and availability of sensitive data packets.

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Publication Details

Published
2024-09-21
DOI
https://doi.org/10.1109/nkcon62728.2024.10774774
Primary Topic
Network Security and Intrusion Detection
Type
article
Field-Weighted Citation Impact
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article

Secure IoT: Fortifying IoT Security with Support Vector Machines

A. Backia Abinaya, Preethi Kathirvel, S. Janani, S. G. Hymlin Rose
Network Security and Intrusion Detection
article

Secure IoT: Fortifying IoT Security with Support Vector Machines

A. Backia Abinaya, Preethi Kathirvel, S. Janani, S. G. Hymlin Rose
article en

Abstract

The Secure IoT will be a proposed system aim for bolstering the security of Internet supported things (IoT) networks by the innovative application of Supportive Vector Machines (SVMs). As the proliferation of IoT Modules will continues to expand for ensuring the integrity and confidentiality of data packets transmitted within these networks may become paramount. In Traditional security will measures often fall short on detecting sophisticated cyber external-attacks targeting the IoT infrastructures. Secure IoT will addresses this challenging of by harnessing the power of SVMs, a powerful machine Learning-Driven technique, to effective in identify and mitigate potential intrusions. The proposed system may operate by analyzing the vast amounts of data packets generated by IoT Modules by including network traffic patterns, device behavioral activities, and communication protocols. SVMs are will employed to classifying of this data packets into distinct categories, by distinguishing between normal activities and suspicious anomalies indicatives of security breaches. By leveraging SVMs' capability to find optimal hyper planes that separate different classes of data packets, Secure IoT could accurately detect and responding to malicious activities in practical. The Key feature of Secure IoT will include robust anomaly detection capabilities and adaptability to dynamic IoT environments, and scalability to accommodate large-scale IoT deployments. Moreover, the utilization of SVMs will enables the system to handles high-dimensional data packets with efficiency and accuracy in making it suitable for diverse IoT applications across various industries. In proposal, Secure IoT represents a significant advancement in IoT security, by offering a proactive and intelligent defense mechanism against emerging Cyber external-attacks. By leverages Supportive Vector Machines methodology, this proposed system might provide a Comprehensively solution for safeguarding the IoT networks and preserving of the confidentiality, integrity, and availability of sensitive data packets.

Dr. M.G.R. Educational and Research Institute (IN), Periyar Maniammai Institute of Science & Technology (IN), R.M.D. Engineering College
Openalex Percentile: Top 71%
Network Security and Intrusion Detection
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