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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:
10
期:
5
页码:
1056-1069
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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