Design of Network Security Experiment Teaching System Based on Honeypot Technology

被引:0
作者
Zhu, Chen [1 ,2 ]
Li, Qiang [1 ]
Sun, Bin [3 ]
Jin, Xinyu [2 ,3 ]
Zhou, Yusun [4 ]
Xie, Muhan [5 ]
机构
[1] Zhejiang Univ, Polytech Inst, Hangzhou, Peoples R China
[2] Zhejiang Univ, Key Lab Collaborat Sensing & Autonomous Unmanned, Hangzhou, Peoples R China
[3] Zhejiang Univ, Coll Informat Sci & Elect Engn, Hangzhou, Peoples R China
[4] Zhejiang Univ City Coll, Hangzhou, Peoples R China
[5] Zhejiang Univ, Hangzhou, Peoples R China
来源
2022 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS 22) | 2022年
关键词
attack-defense system; honeypot; deep learning; experimental teaching system;
D O I
10.1109/ISCAS48785.2022.9937256
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
IoT information security is an introductory course in network security. 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 support vector machine (SVM), decision tree and other networks to detect intrusion data. And then a visualization platform is established for students to do experiment.
引用
收藏
页码:2132 / 2136
页数:5
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