2690-6791ISSN (Online)
2769-786XISSN (Print)
Volume 13 , Issue 2 , PP: 35-51, 2024 | Cite this article as | XML | Html | PDF | Full Length Article
Raenu Kolandaisamy 1 * , Suhas Gupta 2 , Shashikant Patil 3 , Jaymeel Shah 4 , Abhinav Mishra 5 , N. Gobi 6
Doi: https://doi.org/10.54216/JISIoT.130203
This research introduces an advanced network security methodology based on IoT, combining five innovative algorithms: Dynamic Threat Detection (DTD), Adaptive Intrusion Prevention System (AIPS), Anomaly-Based Security Metrics (ABSM), Context-Aware Firewall (CAF), and Cognitive Security Assessment (CSA). Each algorithm contributes specific functionalities, ranging from real-time threat detection and adaptive policy adjustments to anomaly quantification, contextual rule modifications, and holistic security risk assessments. The ablation study conducted on each algorithm reveals critical components driving their performance, ensuring a deep understanding of their inner workings. The proposed method demonstrates superior performance in accuracy, scalability, usability, and adaptability compared to existing network security methods. Visual representations and a comprehensive evaluation further validate the proposed method's effectiveness, positioning it as an advanced and efficient solution for addressing evolving network security challenges.
security algorithms , threat detection , intrusion prevention, IoT , anomaly detection , firewall , cognitive assessment , machine learning , adaptive monitoring , continuous improvement , network context
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