Lightweight anomaly detection model for UAV networks based on memory-enhanced autoencoders
Papers|更新时间:2024-06-12
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Lightweight anomaly detection model for UAV networks based on memory-enhanced autoencoders
Journal on CommunicationsVol. 45, Issue 4, Pages: 13-26(2024)
作者机构:
1..西安电子科技大学网络与信息安全学院, 陕西 西安 710126
2..军事科学院系统工程研究院, 北京 100070
3..西安电子科技大学计算机科学与技术学院, 陕西 西安 710126
作者简介:
基金信息:
The National Natural Science Foundation of China(62220106004;61972308);Major Research Plan of the National Natural Science Foundation of China(92267204);The Key Research and Development Program of Shaanxi Province(2022KXJ-093;2021ZDLGY07-05);Innovation Capability Support Program of Shaanxi(2023-CX-TD-02)
HU Tianzhu, SHEN Yulong, REN Baoquan, et al. Lightweight anomaly detection model for UAV networks based on memory-enhanced autoencoders[J]. Journal on Communications, 2024, 45(4): 13-26.
DOI:
HU Tianzhu, SHEN Yulong, REN Baoquan, et al. Lightweight anomaly detection model for UAV networks based on memory-enhanced autoencoders[J]. Journal on Communications, 2024, 45(4): 13-26. DOI: 10.11959/j.issn.1000-436x.2024011.
Lightweight anomaly detection model for UAV networks based on memory-enhanced autoencoders