Modeling and performance evaluation of an OpenFlow architecture
Proceedings of the 23rd International Teletraffic Congress
Classification of UDP traffic for DDoS detection
LEET'12 Proceedings of the 5th USENIX conference on Large-Scale Exploits and Emergent Threats
AVANT-GUARD: scalable and vigilant switch flow management in software-defined networks
Proceedings of the 2013 ACM SIGSAC conference on Computer & communications security
Computer Networks: The International Journal of Computer and Telecommunications Networking
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Distributed denial-of-service (DDoS) attacks became one of the main Internet security problems over the last decade, threatening public web servers in particular. Although the DDoS mechanism is widely understood, its detection is a very hard task because of the similarities between normal traffic and useless packets, sent by compromised hosts to their victims. This work presents a lightweight method for DDoS attack detection based on traffic flow features, in which the extraction of such information is made with a very low overhead compared to traditional approaches. This is possible due to the use of the NOX platform which provides a programmatic interface to facilitate the handling of switch information. Other major contributions include the high rate of detection and very low rate of false alarms obtained by flow analysis using Self Organizing Maps.