Strategic Approaches to Intrusion Detection in Cloud-IoT Ecosystem

2Applications of Artificial Intelligence for Early Detection of Cyber Threats in Cloud Networks for IoT Devices: A Sentinel Analysis

Kaushiki Chatterjee¹ and Soumen Santra^2*

¹Department of Computer Science, RCC Institute of Information Technology, Kolkata, India

²Department of Computer Application, Techno International New Town, Kolkata, India

Abstract

Traditional security solutions frequently fall short in this changing context. Thus, integrating Artificial Intelligence (AI) for proactive threat detection in IoT networks is critical. The Internet of Cyber Security Things (IoCST) is a rapidly expanding study, which presents new challenges beyond traditional security methods. Artificial intelligence (AI) has emerged as an effective tool for improving IoT security by enabling advanced threat detection and response capabilities. Artificial intelligence systems can continuously monitor network traffic and device behavior, providing real-time insights and alerts. AI can also detect anomalies via pattern recognition, allowing machine learning models to learn typical IoT device behavior patterns. Behavioral analysis aids in the detection of abnormalities such as odd access times, unexpected data transfers, or atypical command sequences. Through pattern recognition, AI can also identify anomalies, enabling machine learning models to pick up on the typical behavior patterns of Internet of Things (IoT) devices. Irregularities like odd access times, unexpected data transfers, or strange ...