Multi-source information comprehensive malicious domain name detection based on convolutional neural network-Reference-Cited by-同舟云学术

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Multi-source information comprehensive malicious domain name detection based on convolutional neural network

Published:2023-12-22 Issue: Volume:30 Page:57-62
ISSN:
Container-title:2023 6th International Conference on Algorithms, Computing and Artificial Intelligence
language:
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Author:

Xie Pei-Yuan¹^ORCID,Wu Jin-Bo¹^ORCID,Zhou Fan¹^ORCID,Xiao Biao²^ORCID

Affiliation:

1. Hunan Electric Power Co. Ltd, China

2. Chinese Academy of Sciences, Computer Network Information Center, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3639631.3639642

Reference21 articles.

1. China Internet Network Information Center. 49 times China Internet network development state statistic report [EB/OL]. http://www.cnnic.cn/gywm/xwzx/rdxw/20172017_7086/202202/t20220225_71724.htm, 2022-02-25.

2. Network Security Information and trends weekly report. The 13th Internet Security Threat Report [EB/OL]. [2018-04-01]. http: / /www. cert. org. cn /publish /main / 44/2018/20180404150414268888501/20180404150414268888501_201html.

3. Guangxi YU Yan ZHANG Huajun CUI Xinghua YANG Yang LI Chang LIU. Design and Implementation of A DGA Domain Name Detection System by Machine Learning[J].Journal of Cyber Security 2020 5(3):35-47.

4. System to discover phishing attacks actively based on DNS[J];Bo Hong;Computer Application Research,2013

5. Congxian Yin. Research and implementation of malicious domain name detection technology based on big Data analysis [D]. Beijing: Beijing University of Posts and Telecommunications,2018.

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