On the Collaborative Inference of DDoS: An Information-theoretic Distributed Approach
Ouerfelli Fatima Ezzahra, Khaled Barbaria, Elias Bou‐Harb, Claude Fachkha, Belhassen Zouari · 2018
Literature contributions have shown that information theoretic techniques can effectively detect various types of Distributed Denial of Service (DDoS) attacks. However, such techniques are often centralized with a limited measurement vantage point and suffer from the issue of single point of failure. Furthermore, with the flourishing of distributed and cloudbased environments, such techniques ought to adapt to such settings for scalability and performance reasons. In this paper, we address the problem of collaborative DDoS detection using information-theoretic techniques. To this end, we propose an entropy-based detection mechanism that supports collaborative agreement to identify suitable tuning network parameters for distributed DDoS inference in real-time. Empirical evaluations with real DDoS attacks demonstrate that the proposed approach is indeed capable of cooperatively inferring DDoS attacks while achieving resiliency and scalability.