Strategic Approaches to Intrusion Detection in Cloud-IoT Ecosystem

4Navigating the Fog AI-Driven Resilience and Privacy Preservation in Cloud IoT Environments

Bhupendra Panchal^1*, Sarah Joby David¹, Ritika Singh¹, Manini Chhabra¹, Ajay Sharma¹ and Tarannum Khan²

¹School of Computing Science and Engineering, VIT Bhopal University, Bhopal-Indore Highway, Kothrikalan, Sehore, Madhya Pradesh, India

²Computer Science and Engineering, Mahakal Institute of Technology, Ujjain, Madhya Pradesh, India

Abstract

Massive volumes of data are collected, processed, and analyzed in real time at a critical juncture because of the rapid growth of Internet of Things (IoT) technology and the widespread usage of cloud computing. Fog computing allows data processing and storage to be done more efficiently near to the site of data generation. Through local data management, latency and bandwidth consumption are decreased, facilitating analytics and decision-making in real-time. IoT systems’ scalability, performance, and reliability are improved by fog computing, which shifts processing power to the network’s edge. Complicating the security picture is the distributed nature of cloud computing, which positions processing and storage nearer to the many data sources. Because they often lack strong security, IoT devices are vulnerable to a variety of attacks. Common issues include hostile attacks, unauthorized access, and data breaches. Large amounts of sensitive data are processed and stored in IoT cloud systems, which exacerbates these security problems. Technologies ...