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Video s3
    Details
    Presenter(s)
    Qiang Li Headshot
    Display Name
    Qiang Li
    Affiliation
    Affiliation
    University of Electronic Science and Technology of China
    Country
    Author(s)
    Display Name
    Chen Zhu
    Affiliation
    Affiliation
    Institute of Image Communication and Network Engineering, Shanghai Jiao Tong University
    Display Name
    Qiang Li
    Affiliation
    Affiliation
    University of Electronic Science and Technology of China
    Display Name
    Bin Sun
    Affiliation
    Affiliation
    Zhejiang University
    Display Name
    Xinyu Jin
    Affiliation
    Affiliation
    Zhejiang University
    Display Name
    Yusun Zhou
    Affiliation
    Affiliation
    Zhejiang University City College
    Display Name
    Muhan Xie
    Affiliation
    Affiliation
    Zhejiang University
    Abstract

    Safety offensive and defense experiments are the means that students can get in contact with network attacks. Students\' network security protection awareness and information protection capabilities can be improved by offensive and defense experiments. At present, there is a problem with high update costs, insufficient comprehensive, complicated operation, and insufficient operation. A new way is presented in this paper to improve the current offensive exercise experiments, providing training platform for postgraduate industrial Internet security courses. It achieves this by using Generative Adversarial Networks (GAN) in honeypot to generate a virtual data for industrial equipment simulation, and using SVM, decision tree and other networks to detect intrusion data. And then a visualization platform is established for students to do experiment.

    Slides
    • Design of Network Security Experiment Teaching System Based on Honeypot Technology (application/pdf)