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Titlebook: Machine Learning for Cyber Security; 4th International Co Yuan Xu,Hongyang Yan,Jin Li Conference proceedings 2023 The Editor(s) (if applica

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樓主: IU421
31#
發(fā)表于 2025-3-26 23:29:40 | 只看該作者
Guanbiao Lin,Hu Li,Yingying Zhang,Shiyu Peng,Yufeng Wang,Zhenxin Zhang,Jin Li
32#
發(fā)表于 2025-3-27 02:00:50 | 只看該作者
Yuhui Huang,Xin Xie,Weiye Ning,Dengquan Wu,Zixi Li,Hao Yang
33#
發(fā)表于 2025-3-27 08:32:08 | 只看該作者
Yusheng Xu,Xinrong Cao,Rong Hu,Pantea Keikhosrokiani,Zuoyong Li
34#
發(fā)表于 2025-3-27 09:35:58 | 只看該作者
35#
發(fā)表于 2025-3-27 15:17:55 | 只看該作者
36#
發(fā)表于 2025-3-27 20:59:56 | 只看該作者
,Multi-party Secure Comparison of?Strings Based on?Outsourced Computation, carry out multi-party joint analysis and computation, securely and privately complete the full excavation of data value in the process of circulation, sharing, fusion, and calculation, which has become a popular research topic. String comparison is one of the common operations in data processing. T
37#
發(fā)表于 2025-3-28 00:06:12 | 只看該作者
38#
發(fā)表于 2025-3-28 04:22:26 | 只看該作者
Overview of DDoS Attack Research Under SDN,ent centralized control, improving network operation efficiency and simplifying network management. However, SDN is vulnerable to Distributed Denial of Service (DDoS) attacks, especially on the control plane, which affects the whole network. In this paper, DDoS attack detection and defense under SDN
39#
發(fā)表于 2025-3-28 10:06:19 | 只看該作者
A Medical Image Segmentation Method Based on Residual Network and Channel Attention Mechanism,field. However, due to the limitation of traditional convolution operations, Unet cannot realize global semantic information interaction. To address this problem, this paper proposes a deep learning model based on Unet. The proposed model takes the Residual network as the image feature extraction la
40#
發(fā)表于 2025-3-28 13:58:25 | 只看該作者
,Performance Improvement of?Classification Model Based on?Adversarial Sample Generation,r to improve the text filtering ability of the neural network model, it is necessary to make the filtering model learn more bad text feature information, especially the feature information that is not recognized by the filtering model at present. Therefore, having more abundant and diverse high-qual
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