Unsupervised Multi-Target Cross-Service Log Anomaly Detection

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成果类型：

期刊论文

作者：

He, Shiming;Liu, Rui;Chen, Bowen;Xie, Kun;Wen, Jigang

通讯作者：

Xie, K

作者机构：

[Liu, Rui; He, Shiming; Chen, Bowen] Changsha Univ Sci & Technol, Sch Comp Sci & Technol, Changsha 410114, Peoples R China.

[Liu, Rui; He, Shiming; Chen, Bowen] Changsha Univ Sci & Technol, Hunan Prov Key Lab Intelligent Proc Big Data Trans, Changsha 410114, Peoples R China.

[Chen, Bowen] Hunan Prov China Telecom Co Ltd, Beijing 100033, Peoples R China.

[Xie, Kun] Hunan Univ, Coll Comp Sci & Elect Engn, Key Lab Fus Comp Supercomp & Artificial Intelligen, Minist Educ, Changsha 410012, Peoples R China.

[Wen, Jigang] Hunan Univ Sci & Technol, Sch Comp Sci & Engn, Xiangtan 411199, Peoples R China.

通讯机构：

[Xie, K ] H

Hunan Univ, Coll Comp Sci & Elect Engn, Key Lab Fus Comp Supercomp & Artificial Intelligen, Minist Educ, Changsha 410012, Peoples R China.

语种：

英文

关键词：

Anomaly detection;Transfer learning;Adaptation models;Contrastive learning;Deep learning;Training;Semantics;Computational modeling;Training data;Accuracy;Log anomaly detection;contrastive learning;transfer learning;multi-target domain;siamese neural network

期刊：

IEEE TRANSACTIONS ON SUSTAINABLE COMPUTING

ISSN：

2377-3782

年：

2025

卷：

期：

页码：

1056-1069

DOI：

10.1109/TSUSC.2025.3578517

基金类别：

National Natural Science Foundation of China [62272062, 62025201]; Science and Technology Innovation Program of Hunan Province [2023RC3139]; Natural Science Foundation of Hunan Province [2025JJ50373]; Scientific Research Fund of Hunan Provincial Transportation Department [202143]

机构署名：

本校为其他机构

院系归属：

计算机与通信工程学院

摘要：

Log analysis, especially log anomaly detection, can help debug systems and analyze root causes to provide reliable services. Deep learning is a promising technology for log anomaly detection. However, deep learning methods need a large amount of training data, which is hard for a newly deployed system to collect sufficient logs. Transfer learning becomes a possible method to solve the problem that can apply the knowledge from a long-term deployed system (source) to a newly deployed system (target). Existing transfer learning methods focus on transferring the knowledge from a source system to a...

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