DA-Parser: A Pre-trained Domain-aware Parsing Framework for Heterogeneous Log Analysis-Reference-Cited by-同舟云学术

DA-Parser: A Pre-trained Domain-aware Parsing Framework for Heterogeneous Log Analysis

Published:2023-06 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE 47th Annual Computers, Software, and Applications Conference (COMPSAC)
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Author:

Tao Shimin¹,Liu Yilun²,Meng Weibin²,Wang Jingyu³,Zhao Yanqing²,Su Chang²,Tian Weinan²,Zhang Min²,Yang Hao²,Chen Xun¹

Affiliation:

1. University of Science and Technology of China,China

2. Huawei,China

3. Beijing University of Posts and Telecommunications,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10196792/10196808/10196816.pdf?arnumber=10196816

Reference26 articles.

1. An empirical study of the impact of log parsers on the performance of log-based anomaly detection

2. Clustering event logs using iterative partitioning

3. Huma: A multilayer framework for threat analysis in a heterogeneous log environment;navarro;Intemationsal Symposium on Foundations and Practice of Security,2017

4. Semparser: A semantic parser for log analysis;huo,2021

5. Spell: Streaming Parsing of System Event Logs

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3. Multi-Source Log Parsing With Pre-Trained Domain Classifier;IEEE Transactions on Network and Service Management;2023