Using the SGE-CGAM Method to Address Class Imbalance Issues in Network Intrusion Detection
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-9788-6_15
Reference10 articles.
1. Gu, L., Sun, H., Zhao, X., Wang, L.: A distributed intrusion detection system based on CNN-GRU in cloud environment. In: International Conference on Artificial Intelligence and Intelligent Information Processing (AIIIP 2022), vol. 12456, pp. 167–173. SPIE (2022)
2. Sun, P.: Dl-IDS: extracting features using CNN-LSTM hybrid network for intrusion detection system. Secur. Commun. Networks 1–11, 2020 (2020)
3. Liu, H., Lang, B.: Machine learning and deep learning methods for intrusion detection systems: a survey. Appl. Sci. 9(20), 4396 (2019)
4. Sharafaldin, I., Lashkari, A.H., Ghorbani, A.A.: Toward generating a new intrusion detection dataset and intrusion traffic characterization. In: Proceedings of the 4th International Conference on Information Systems Security and Privacy (ICISSP 2018), pp. 108–116 (2018)
5. Sharafaldin, I., Gharib, A., Lashkari, A.H., Ghorbani, A.A.: Towards a reliable intrusion detection benchmark dataset. Softw. Networking 2017(1), 177–200 (2017)
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