An APT Malware Classification Method Based on Adaboost Feature Selection and LightGBM

Author:

Xu Na1,Li Shudong1,Wu Xiaobo2,Han Weihong1,Luo Xiaojing1

Affiliation:

1. Cyberspace Institute of Advanced Technology, Guangzhou University,Guangzhou,China

2. School of Computer Science and Cyber Engineering, Guangzhou University,Guangzhou,China

Funder

NSFC

National Key Research and Development Program of China

Publisher

IEEE

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Research on APT Malware Detection Based on BERT-Transformer-TextCNN Modeling;Proceedings of the 2024 International Conference on Generative Artificial Intelligence and Information Security;2024-05-10

2. Anomalous traffic detection algorithm for SDN;2023 IEEE 2nd Industrial Electronics Society Annual On-Line Conference (ONCON);2023-12-08

3. Building APT Malicious Attacker Profiles for Power Monitoring Systems with Machine Learning;2023 4th International Conference on Advanced Electrical and Energy Systems (AEES);2023-12-01

4. Understanding the Threat Posed by Chinese Cyber Warfare Units;2023 IEEE 3rd International Maghreb Meeting of the Conference on Sciences and Techniques of Automatic Control and Computer Engineering (MI-STA);2023-05-21

5. A Review of Provenance Graph based APT Attack Detection:Applications and Developments;2022 7th IEEE International Conference on Data Science in Cyberspace (DSC);2022-07

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