Hybrid Collaborative Architectures For Intrusion Detection In Multi-Access Edge Computing
Rahul Sharma, Chien Aun Chan, Christopher A. Leckie · NOMS 2022-2022 IEEE/IFIP Network Operations and Management Symposium · 2022
Multi-Access Edge Computing (MEC) provides high network bandwidth and ultra-low latency response time but also inherits the security vulnerabilities of cloud computing to Distributed Denial of Service (DDoS) attacks. To guard MEC nodes from such attacks, previous work has proposed the use of Collaborative Intrusion Detection Systems (CIDS) as a prime candidate for attack detection. Our previous work looked at Centralised and Distributed CIDS architectures and identified some shortcomings in them. In this paper, we address these shortcomings by presenting a purely edge-based novel Hybrid CIDS architecture, and its improvement using an exponential threshold mechanism. We assess the performance of our novel architectures through experimentation on a real-world worm dataset based on detection accuracy, bandwidth utilisation, and CPU and memory usage, and compare against benchmark performance results for the Centralised and the Distributed CIDS architectures proposed previously. Following this, we present the performance metrics of our novel architectures during node failure events and outline their resilience to such failures.