DDoS Attacks on Cloud Auto-scaling Mechanisms
Auto-scaling mechanisms are an important line of defense against distributed denial of service (DDoS) attacks in the cloud. Using auto-scaling, machines can be added and removed in an online manner to respond to fluctuating load. It is commonly believed that the auto-scaling mechanism casts DDoS attacks into Economic Denial of Sustainability (EDoS) attacks. Rather than suffering from performance degradation up to a total denial of service, the victim suffers from the economic damage incurred by paying for the extra resources required to process the bogus traffic of the attack. In this project, we aim to study DDoS/EDoS attacks that violate the above belief by causing both significant performance degradation and economic damage. During one such attack, known as Yo-Yo, an attacker repeatedly oscillates between sending a burst of traffic (thus causing a scale-up) and stopping the burst (causing a scale-down as s result). Our goal is to thoroughly evaluate the damage potential of Yo-Yo and similar attacks, as well as to devise novel detection and mitigation mechanisms for platforms such as Kubernetes.