期刊
INFORMATION SCIENCES
卷 513, 期 -, 页码 65-83出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.ins.2019.08.047
关键词
Network attack detection; Data-driven; Tensor; Network security; Software defined network (SDN)
资金
- National Key Research & Development Plan of China [2017YFB0801804]
- Shenzhen Fundamental Research Program [JCYJ20170307172200714]
- Fundamental Research Funds for the Central Universities [HUST2018KFYXKJC046]
SDN (Software Defined Network) has emerged as a revolutionary technology in network, a substantial amount of researches have been dedicated to security of SDNs to support their various applications. The paper firstly analyzes State-of-the-Art of SDN security from data perspectives. Then some typical network attack detection (NAD) methods are surveyed, including machine learning based methods and statistical methods. After that, a novel tensor based network attack detection method named tensor principal component analysis (TPCA) is proposed to detect attacks. After surveying the last data-driven SDN frameworks, a tensor based big data-driven SDN attack detection framework is proposed for SDN security. In the end, a case study is illustrated to verify the effectiveness of the proposed framework. (C) 2019 Elsevier Inc. All rights reserved.
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