Literature Review on Log Anomaly Detection Approaches Utilizing Online Parsing Methodology∗

研究成果: Conference contribution

抄録

The use of anomaly detection for log monitoring requires parsing model input features from raw, unstructured data. Log parsing methods come in many forms, but are generally categorized as being either offline or online. In this study, a systematic literature review of anomaly detection approaches utilizing online parsing methods is performed. An inventory of these approaches is taken, research gaps are explored, and suggestions for future exploration and study are presented.

本文言語English
ホスト出版物のタイトルProceedings - 2021 28th Asia-Pacific Software Engineering Conference, APSEC 2021
出版社IEEE Computer Society
ページ559-563
ページ数5
ISBN(電子版)9781665437844
DOI
出版ステータスPublished - 2021
イベント28th Asia-Pacific Software Engineering Conference, APSEC 2021 - Virtual, Online, Taiwan, Province of China
継続期間: 2021 12月 62021 12月 9

出版物シリーズ

名前Proceedings - Asia-Pacific Software Engineering Conference, APSEC
2021-December
ISSN(印刷版)1530-1362

Conference

Conference28th Asia-Pacific Software Engineering Conference, APSEC 2021
国/地域Taiwan, Province of China
CityVirtual, Online
Period21/12/621/12/9

ASJC Scopus subject areas

  • ソフトウェア

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引用スタイル