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CAE-IF:An Anomaly Detection Approach Based on Temporal Representation of the Reconstruction Error

Haijun Geng Zhi Zhang Yuhua Qian Bo Yang Qi Ma Haotian Chi Jing Yang Xia Yin

清华大学学报自然科学版（英文版）2026，Vol.31Issue(4)：2055-2070,16.

清华大学学报自然科学版（英文版）2026，Vol.31Issue(4)：2055-2070,16.DOI:10.26599/TST.2024.9010215

CAE-IF:An Anomaly Detection Approach Based on Temporal Representation of the Reconstruction Error

Haijun Geng ¹Zhi Zhang ²Yuhua Qian ³Bo Yang ⁴Qi Ma ²Haotian Chi ²Jing Yang ²Xia Yin⁵

作者信息

1. School of Automation and Software Engineering,Shanxi University,Taiyuan 030006,China||Shanxi Qingzhong Technology Co.Ltd.,Taiyuan 030032,China
2. School of Automation and Software Engineering,Shanxi University,Taiyuan 030006,China
3. Institute of Big Data Science and Industry,Shanxi University,Taiyuan 030006,China
4. Department of Urban & Regional Planning San José State University,San José,CA 95192,USA
5. Department of Computer Science and Technology,Tsinghua University,Beijing 100084,China
折叠

摘要

关键词

unsupervised learning/network traffic detection/reconstruction error/temporal representation

Key words

unsupervised learning/network traffic detection/reconstruction error/temporal representation

引用本文复制引用

Haijun Geng,Zhi Zhang,Yuhua Qian,Bo Yang,Qi Ma,Haotian Chi,Jing Yang,Xia Yin..CAE-IF:An Anomaly Detection Approach Based on Temporal Representation of the Reconstruction Error[J].清华大学学报自然科学版（英文版）,2026,31(4):2055-2070,16.

基金项目

This work was in part supported by the National Natural Science Foundation of China(Nos.62472267,62302282,and 62406181),the Shanxi Province Science Foundation(Nos.202203021222005 and 202203021222010),the Postgraduate Research Innovation Program of Shanxi Province(No.2024KY137),and the Scientific and Technological Innovation 2030—"New Generation Artificial Intelligence"Major Project(No.2021ZD0112400). （Nos.62472267,62302282,and 62406181）

清华大学学报自然科学版（英文版）

ISSN：1007-0214

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