Traffic-based Malicious Switch Detection in SDN

被引:3
|
作者
Du, Xiaodong [1 ]
Wang, Ming-Zhong [1 ]
Zhang, Xiaoping [2 ]
Zhu, Liehuang [1 ]
机构
[1] Beijing Inst Technol, Beijing Engn Res Ctr Mass Language Informat Proc, Sch Comp Sci, Beijing, Peoples R China
[2] China North Vehicle Res Inst, Natl Key Lab Vehicular Transmiss, Beijing, Peoples R China
基金
北京市自然科学基金; 美国国家科学基金会;
关键词
SDN; OpenFlow; malicious switch; detection;
D O I
10.14257/ijsia.2014.8.5.12
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In Software Defined Networking (SDN) architecture, the control plane is separated from the data plane. On one hand, OpenFlow switches can only store and forward packets, which leaves all decisions to be made by the controller. On the other hand, the controller has a global view over the SDN. But if any switch is captured by an adversary, it may mislead the controller to make inaccurate decisions which may have terrible influences on the overall networks. In this paper, we elaborate on these problems and propose methods to detect malicious OpenFlow switches. We set a threshold value of the traffic-flows across an OpenFlow switch. If the switch's current traffic-flows exceed the threshold value, the controller has reasons to believe that this switch is suspicious and may monitor it intensively. Another scheme is to add a third-party server to accept users' report to warn the controller. In SDN, the controller cannot communicate with users directly, and sometimes users need to feed back their experience to the controller to help improve the SDN. In this case, it is necessary to set a third-party server in SDN to act as a middle role. These two schemes help to detect malicious switches. The controller can analyze the flow table of the suspicious switch and identify whether it is really malicious before isolating it.
引用
收藏
页码:119 / 130
页数:12
相关论文
共 50 条
  • [41] A traffic-based routing algorithm by using mobile agents
    Wenyu Qu
    Masaru Kitsuregawa
    Hai Zhuge
    Hong Shen
    Yinwei Jin
    COMPUTER SYSTEMS SCIENCE AND ENGINEERING, 2007, 22 (06): : 323 - 332
  • [42] Encrypted Malicious Traffic Detection Based on Word2Vec
    Ferriyan, Andrey
    Thamrin, Achmad Husni
    Takeda, Keiji
    Murai, Jun
    ELECTRONICS, 2022, 11 (05)
  • [43] Intelligent detection method on network malicious traffic based on sample enhancement
    Chen T.
    Jin C.
    Lyu M.
    Zhu T.
    2020, Editorial Board of Journal on Communications (41): : 128 - 138
  • [44] Malicious attack detection based on traffic-flow information fusion
    Chen, Ye
    Lai, Yingxu
    Zhang, Zhaoyi
    Li, Hanmei
    Wang, Yuhang
    2022 IFIP NETWORKING CONFERENCE (IFIP NETWORKING), 2022,
  • [45] MalFinder: An Ensemble Learning-based Framework For Malicious Traffic Detection
    Rong, Candong
    Gou, Gaopeng
    Cui, Mingxin
    Xiong, Gang
    Li, Zhen
    Guo, Li
    2020 IEEE SYMPOSIUM ON COMPUTERS AND COMMUNICATIONS (ISCC), 2020, : 588 - 594
  • [46] BoAu: Malicious traffic detection with noise labels based on boundary augmentation
    Yuan, Qingjun
    Liu, Chang
    Yu, Wentao
    Zhu, Yuefei
    Xiong, Gang
    Wang, Yongjuan
    Gou, Gaopeng
    COMPUTERS & SECURITY, 2023, 131
  • [47] Anomalous traffic detection algorithm for SDN
    Zheng Siqi
    Fu Yanfang
    Yan Guochuang
    Du Zhiqiang
    Cao Zijian
    2023 IEEE 2ND INDUSTRIAL ELECTRONICS SOCIETY ANNUAL ON-LINE CONFERENCE, ONCON, 2023,
  • [48] Adversarial Malicious Encrypted Traffic Detection Based on Refined Session Analysis
    Li, Minghui
    Wu, Zhendong
    Chen, Keming
    Wang, Wenhai
    SYMMETRY-BASEL, 2022, 14 (11):
  • [49] PIoT Malicious Traffic Detection Method Based on GAN Sample Enhancement
    Hou, Botao
    Zhang, Ke
    Zuo, Xiaojun
    Zhao, Jianli
    Xi, Bo
    SECURITY AND COMMUNICATION NETWORKS, 2022, 2022
  • [50] Energy Efficient Traffic-Based Street Lighting Automation
    Nefedov, Evgeny
    Maksimainen, Mikko
    Sierla, Seppo
    Yang, Chen-Wei
    Flikkema, Paul
    Kosonen, Iisakki
    Luttinen, Tapio
    2014 IEEE 23RD INTERNATIONAL SYMPOSIUM ON INDUSTRIAL ELECTRONICS (ISIE), 2014, : 1718 - 1723