CSCAD: Correlation Structure-Based Collective Anomaly Detection in Complex System

Detecting anomalies in large complex systems is a critical and challenging task. The difficulties arise from several aspects. First, collecting ground truth labels or prior knowledge for anomalies is hard in real-world systems, which often lead to limited or no anomaly labels in the dataset. Second,...

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Bibliographic Details
Published in:	IEEE transactions on knowledge and data engineering Vol. 35; no. 5; pp. 4634 - 4645
Main Authors:	Qin, Huiling, Zhan, Xianyuan, Zheng, Yu
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.05.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Algorithms Anomalies Anomaly detection complex system Complex systems Correlation correlation mining Data models Datasets Feature extraction Labels Loss measurement Reconstruction Sensors unsupervised learning urban computing variational autoencoder
ISSN:	1041-4347, 1558-2191
Online Access:	Get full text
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