Anomaly Detection in Multivariate Time Series with Contaminated Training Data Using VAE

• Published in: 2024 IEEE 10th Conference on Big Data Security on Cloud (BigDataSecurity) pp. 5 - 10
• Main Authors: Lv, Dongfeng, Ma, Manman, Dong, Hanxia, Shang, Yishan, Bao, Kuo
• Format: Conference Proceeding
• Language: English
• Published: IEEE 10.05.2024
• Subjects: anomaly detection; Data models; Deep learning; multivariate time series; Noise measurement; noisy data; pseudo label; Security; Time series analysis; Training; Training data; variational autoencoder

Multivariate time series anomaly detection (MVT-SAD) is a significant data mining task with numerous applications in the IoT era. Nowadays, with the advancement of deep learning technology, an increasing number of deep learning models have made significant progress in the MVTSAD field compared to tr...