Cyber Edge: Mitigating Cyber-Attacks in Edge Computing Using Intrusion Detection System

Edge computing, an extension of cloud and IoT technologies, introduces unique challenges for intrusion-detection systems (IDS). This study explores IDS architecture in the context of edge computing. We proposed a specialized IDS architecture for edge environments, serving as the foundation for resource allocation strategies. Our chosen allocation model, the single-layer dominant and max-min fair (SDMMF), is theoretically validated to meet hierarchical resource allocation principles. Additionally, we introduce the multilayer dominant and max-min fair (MDMMF) allocation scheme to ensure equitable resource distribution across multiple layers. This research contributes to the enhancement of resource allocation methodologies within IDS, bolstering IoT security in the dynamic edge computing landscape. Given the increasing significance of edge computing, optimizing resource allocation within IDS is crucial for safeguarding critical systems.