Prediction, Detection, and Mitigation of DDoS Attacks Using HPCs

Abstract

Web service interruptions caused by DDoS (distributed denial of service) attacks have increased considerably over the years, and intrusion detection systems (IDS) are not enough to detect threats on the network, even when used together with intrusion prevention systems (IPS), taking into account the increase of assets in the traffic path, where it creates unique points of failure in the system, and also taking into account the use of data that contains information about normal traffic situations and attacks, where this comparison and analysis can cost a significant amount of host resources, to try to guarantee the prediction, detection, and mitigation of attacks in real-time or in time between detection and mitigation, being crucial in harm reduction. This chapter presents an adaptive architecture that combines techniques, methods, and tools from different segments to improve detection accuracy as well as the prediction and mitigation of these threats and to show that it is capable of implementing a powerful architecture against this type of threat, DDoS attacks.