Service resizing for quick DDoS mitigation in cloud computing environment
Current trends in distributed denial of service (DDoS) attacks show variations in terms of attack motivation, planning, infrastructure, and scale. "DDoS for Hire" and "DDoS mitigation as a Service" are the two services, which are available to attackers and victims, respectively. In this work, we provide a fundamental difference between a "regular" DDoS attack and an "extreme" DDoS attack. We conduct DDoS attacks on cloud services, where having the same attack features, two different services show completely different consequences, due to the difference in the resource utilization per request. We study various aspects of these attacks and find out that the DDoS mitigation service's performance is dependent on two factors. One factor is related to the severity of the "resource race" with the victim web service. Second factor is "attack cooling down period" which is the time taken to bring the service availability post detection of the attack. Utilizing these two important factors, we propose a supporting framework for the DDoS mitigation services, by assisting in reducing the attack mitigation time and the overall downtime. This novel framework comprises of an affinity based victim service resizing algorithm to provide performance isolation, and a TCP tuning technique to quickly free the attack connections, hence minimizing the attack cooling down period. We evaluate the proposed novel techniques with real attack instances and compare various attack metrics. Results show a significant improvement to the performance of DDoS mitigation service, providing quick attack mitigation. The presence of proposed DDoS mitigation support framework demonstrated a major reduction of more than 50% in the service downtime.
Ann. des Telecommunications