commute
发表于 2025-3-23 12:09:00
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松软无力
发表于 2025-3-23 15:00:21
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Mercurial
发表于 2025-3-23 20:15:42
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Yag-Capsulotomy
发表于 2025-3-24 01:31:12
David H. Kelley,Eugene F. Milonee widespread proliferation of the internet and the rapid evolution of information technology, network intrusions have become increasingly commonplace and intricate, underscoring the growing significance of network intrusion detection. In order to enhance the performance of network intrusion detectio
Oafishness
发表于 2025-3-24 02:25:37
David H. Kelley,Eugene F. Miloness imbalance within intrusion detection datasets hampers the classifier’s performance on minority classes. To simultaneously improve detection precision while maintaining efficiency, we introduce an innovative approach for addressing class imbalance in extensive datasets, denoted as SGE (SMOTE-Gauss
幻想
发表于 2025-3-24 09:42:19
Observational Methods and Problemsical value in preventing and managing events such as traffic congestion and accidents. However, effectively distributing beacon messages in complex and dynamic traffic environments presents a major challenge. Therefore, this paper introduces VANETs, where the strategy for communication link duration
Institution
发表于 2025-3-24 11:24:05
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多嘴多舌
发表于 2025-3-24 17:08:50
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Agronomy
发表于 2025-3-24 21:58:44
David H. Kelley,Eugene F. Milone in learning the anomaly information. At the same time, the current mainstream detection methods all need help with the problems of limited feature learning ability and weak model generalization ability. Therefore, this paper proposes a multi-module combination of anomaly detection and localization
habitat
发表于 2025-3-25 02:47:35
https://doi.org/10.1007/978-981-99-9788-6Machine learning; Adversarial machine learning; Malware detection and analysis; Privacy-preserving data