Cognitive Sentinel: Dynamic Defense against Malicious Fog Nodes in Evolving Fog -2- fog Collaborative Models

Abstract

Many time-sensitive IoT applications require low latency and achieving other Quality of Service (QoS) criteria proves challenging with conventional cloud computing. To address these issues, Cisco introduced Fog Computing in 2015. However, the dynamic nature of the fog computing environment introduces several securi ty challenges. Compounding the issue, fog nodes are often deployed by different vendors with varying security policies. Collaboration among fog nodes, especially in data offloading scenarios, presents security concerns that are currently underexplored. The existing work on security in fog computing is limited, and conventional cryptography strategies are ill-suited for detecting malicious fog nodes within the network. Consequently, the presence of malicious nodes poses threats to the reputation of IoT services and compromises user privacy. This thesis advocates for a trust -based approach, aiming to identify the most trustworthy node for offloading tasks while isolating any malicious nodes within the fog domain. By doing so, our proposed approach enhances inside network security and elevates overall Quality of Service (QoS).