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DDoS Attack Detection and Mitigation Using SDN: Methods, Practices, and Solutions

  • Review Article - Computer Engineering and Computer Science
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Abstract

Distributed denial-of-service (DDoS) attacks have become a weapon of choice for hackers, cyber extortionists, and cyber terrorists. These attacks can swiftly incapacitate a victim, causing huge revenue losses. Despite the large number of traditional mitigation solutions that exists today, DDoS attacks continue to grow in frequency, volume, and severity. This calls for a new network paradigm to address the requirements of today’s challenging security threats. Software-defined networking (SDN) is an emerging network paradigm which has gained significant traction by many researchers to address the requirement of today’s data centers. Inspired by the capabilities of SDN, we present a comprehensive survey of existing SDN-based DDoS attack detection and mitigation solutions. We classify solutions based on DDoS attack detection techniques and identify requirements of an effective solution. Based on our findings, we propose a novel framework for detection and mitigation of DDoS attacks in a large-scale network which comprises a smart city built on SDN infrastructure. Our proposed framework is capable of meeting application-specific DDoS attack detection and mitigation requirements. The primary contribution of this paper is twofold. First, we provide an in-depth survey and discussion of SDN-based DDoS attack detection and mitigation mechanisms, and we classify them with respect to the detection techniques. Second, leveraging the characteristics of SDN for network security, we propose and present an SDN-based proactive DDoS Defense Framework (ProDefense). We show how this framework can be utilized to secure applications built for smart cities. Moreover, the paper highlights open research challenges, future research directions, and recommendations related to SDN-based DDoS detection and mitigation.

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Authors and Affiliations

  1. Systems Research Laboratory, FAST-National University of Computer and Emerging Sciences, Karachi, Pakistan

    Narmeen Zakaria Bawany & Jawwad A. Shamsi

  2. Electrical and Computer Engineering Department, Khalifa University of Science, Technology and Research, PO Box 573, Sharjah, UAE

    Khaled Salah

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  1. Narmeen Zakaria Bawany
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  2. Jawwad A. Shamsi
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  3. Khaled Salah
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Bawany, N.Z., Shamsi, J.A. & Salah, K. DDoS Attack Detection and Mitigation Using SDN: Methods, Practices, and Solutions. Arab J Sci Eng 42, 425–441 (2017). https://doi.org/10.1007/s13369-017-2414-5

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