Selective ensemble of KELM-based complex network intrusion detection

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Network anomaly detection technology based on deep learning

AD Eunice, Q Gao, MY Zhu, Z Chen… - 2021 IEEE 3rd …, 2021 - ieeexplore.ieee.org
To improve the accuracy and real-time performance of anomaly detection models in
complex network environments, a network anomaly detection model based on random forest …
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A weighted intrusion detection model of dynamic selection

T Feng, M Dou - Applied Intelligence, 2021 - Springer
In view of the difficulty of existing intrusion detection methods in dealing with new forms,
large scale, and high concealment of network intrusion behaviors, this paper presents a …
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A universal intelligent method for intrusion detection

Y Wang, J **, M Zhong - Journal of Cyber Security Technology, 2022 - Taylor & Francis
Machine learning algorithms have been widely used in the field of intrusion detection, which
effectively improves the detection effect. However, with changeable attack methods and the …
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A Cyber Security Situational Awareness Extraction Method Oriented to Imbalanced Samples

K Yin, Y Yang, C Yao - The International Conference on Image, Vision and …, 2022 - Springer
Due to the cyber security data contains a small proportion of attack data that cannot be
effectively detected, and it is difficult for the traditional cyber security situation element …
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面向样本不**衡的网络安全态势要素获取.

张欣， 朱江 - Journal of Computer Engineering & …, 2022 - search.ebscohost.com
针对传统的网络安全态势要素获取模型中, 当样本分布不**衡时, 占比很少的样本(统称小样本)
不能被有效检测, 准确识别到每一类攻击样本成为研究热点之一. 利用深度学**提出了一种面向 …
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[CITAT][C] Network intrusion detection model based on random forest and XGBoost

C Zhuo, L Na - 信号处理, 2020 - 信号处理
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