Joint DDoS detection system based on software-defined networking

SONG Yubo; YANG Huiwen; WU Wei; HU Aiqun; GAO Shang

doi:10.16511/j.cnki.qhdxxb.2018.26.049

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Journal of Tsinghua University(Science and Technology) ›› 2019, Vol. 59 ›› Issue (1) : 28-35. DOI: 10.16511/j.cnki.qhdxxb.2018.26.049

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Joint DDoS detection system based on software-defined networking

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Abstract

Distributed denial-of-service (DDoS) attacks, which are becoming increasingly serious, have become one of the biggest threats to network security. Traditional defense mechanisms such as instruction detection, traffic filtering and multiple authentication are limited to static networks, which leads to obvious drawbacks. Software-defined networking (SDN) is a typical dynamic network that provides defenses against DDoS. The existing SDN-based DDoS protection solutions are still in development with many problems that need improvement. A DDoS detection scheme combined with trigger detection and in-depth detection is given here to shorten the detection period with low system overhead. A low-overhead, coarse-grained trigger detection algorithm is integrated with a precise, fine-grained, in-depth detection algorithm to reduce system complexity while ensuring high detection accuracy. An SDN DDoS detection system has been implemented on the Mininet platform to test and evaluate the system. The test show that the detection system has low system overhead, high detection accuracy, and strong practical value.

Key words

distributed denial-of-service attack / software-defined networking / anomaly detection / ensemble learning

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SONG Yubo, YANG Huiwen, WU Wei, HU Aiqun, GAO Shang. Joint DDoS detection system based on software-defined networking[J]. Journal of Tsinghua University(Science and Technology). 2019, 59(1): 28-35 https://doi.org/10.16511/j.cnki.qhdxxb.2018.26.049

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