Leveraging large language models and BERT for log parsing and anomaly detection
Computer systems and applications generate large amounts of logs to measure and record information, which is vital to protect the systems from malicious attacks and useful for repairing faults, especially with the rapid development of distributed computing. Among various logs, the anomaly log is ben...
Main Authors: | Zhou, Yihan, Chen, Yan, Rao, Xuanming, Zhou, Yukang, Li, Yuxin, Hu, Chao |
---|---|
Other Authors: | School of Computer Science and Engineering |
Format: | Journal Article |
Language: | English |
Published: |
2024
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/181426 |
Similar Items
-
Phase Fourier Reconstruction for Anomaly Detection on Metal Surface Using Salient Irregularity
by: Hung, Tzu-Yi, et al.
Published: (2017) -
Contextual object detection with multimodal large language models
by: Zang, Yuhang, et al.
Published: (2024) -
Advances and applications of large language models II
by: Ng, Qi Xuan
Published: (2024) -
Bayesian dynamic programming approach for tracking time-varying model properties in SHM
by: Yang, Yanping, et al.
Published: (2022) -
MCQGen: a large language model-driven MCQ generator for personalized learning
by: Hang, Ching Nam, et al.
Published: (2024)