Log Sequence Anomaly Detection Method Based on Contrastive Adversarial Training and Dual Feature Extraction

• Published in: Entropy (Basel, Switzerland) Vol. 24; no. 1; p. 69
• Main Authors: Wang, Qiaozheng, Zhang, Xiuguo, Wang, Xuejie, Cao, Zhiying
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 30.12.2021; MDPI
• Subjects: Abnormalities; Accuracy; adversarial training; Anomalies; Artificial intelligence; BERT; Coders; contrastive learning; Deep learning; Feature extraction; Machine learning; Messages; Performance evaluation; Semantics; Software; statistical features; Support vector machines; Training; VAE; contrastive learning; BERT; adversarial training; VAE; statistical features

The log messages generated in the system reflect the state of the system at all times. The realization of autonomous detection of abnormalities in log messages can help operators find abnormalities in time and provide a basis for analyzing the causes of abnormalities. First, this paper proposes a lo...