当前位置：
X-MOL 学术
›
IEEE Trans. Inform. Forensics Secur.
›
论文详情
Our official English website, www.x-mol.net, welcomes your
feedback! (Note: you will need to create a separate account there.)
Fed-UGI: Federated Undersampling Learning Framework with Gini Impurity for Imbalanced Network Intrusion Detection
IEEE Transactions on Information Forensics and Security ( IF 6.3 ) Pub Date : 2024-12-12 , DOI: 10.1109/tifs.2024.3516547 Ming Zheng, Xiaowen Hu, Ying Hu, Xiaoyao Zheng, Yonglong Luo
中文翻译：
Fed-UGI： 用于不平衡网络入侵检测的具有基尼杂质的联邦欠采样学习框架
更新日期：2024-12-12
IEEE Transactions on Information Forensics and Security ( IF 6.3 ) Pub Date : 2024-12-12 , DOI: 10.1109/tifs.2024.3516547 Ming Zheng, Xiaowen Hu, Ying Hu, Xiaoyao Zheng, Yonglong Luo
中文翻译：
Fed-UGI： 用于不平衡网络入侵检测的具有基尼杂质的联邦欠采样学习框架
京公网安备 11010802027423号