Log File Analysis Based on Machine Learning: A Survey
In the past few years, software monitoring and log analysis become very interesting topics because it supports developers during software developing, identify problems with software systems and solving some of security issues. A log file is a computer-generated data file which provides information o...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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University of Human Development
2022-10-01
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| Series: | UHD Journal of Science and Technology |
| Subjects: | |
| Online Access: | https://journals.uhd.edu.iq/index.php/uhdjst/article/view/994 |
| _version_ | 1828069339973025792 |
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| author | Rawand Raouf Abdalla Alaa Khalil Jumaa |
| author_facet | Rawand Raouf Abdalla Alaa Khalil Jumaa |
| author_sort | Rawand Raouf Abdalla |
| collection | DOAJ |
| description | In the past few years, software monitoring and log analysis become very interesting topics because it supports developers during software developing, identify problems with software systems and solving some of security issues. A log file is a computer-generated data file which provides information on use patterns, activities, and processes occurring within an operating system, application, server, or other devices. The traditional manual log inspection and analysis became impractical and almost impossible due logs’ nature as unstructured, to address this challenge, Machine Learning (ML) is regarded as a reliable solution to analyze log files automatically. This survey tries to explore the existing ML approaches and techniques which are utilized in analyzing log file types. It retrieves and presents the existing relevant studies from different scholar databases, then delivers a detailed comparison among them. It also thoroughly reviews utilized ML techniques in inspecting log files and defines the existing challenges and obstacles for this domain that requires further improvements. |
| first_indexed | 2024-04-11T00:17:34Z |
| format | Article |
| id | doaj.art-71a58d7424ea4a4fafa61c8db1101f6f |
| institution | Directory Open Access Journal |
| issn | 2521-4209 2521-4217 |
| language | English |
| last_indexed | 2024-04-11T00:17:34Z |
| publishDate | 2022-10-01 |
| publisher | University of Human Development |
| record_format | Article |
| series | UHD Journal of Science and Technology |
| spelling | doaj.art-71a58d7424ea4a4fafa61c8db1101f6f2023-01-08T19:42:55ZengUniversity of Human DevelopmentUHD Journal of Science and Technology2521-42092521-42172022-10-0162778410.21928/uhdjst.v6n2y2022.pp77-841125Log File Analysis Based on Machine Learning: A SurveyRawand Raouf Abdalla0Alaa Khalil Jumaa1-Department of Information Technology, Technical College of Informatics, Sulaimani Polytechnic University, Sulaimani, Kurdistan Region, IraqDepartment of Information Technology, Technical College of Informatics, Sulaimani Polytechnic University, Sulaimani, Kurdistan Region, IraqIn the past few years, software monitoring and log analysis become very interesting topics because it supports developers during software developing, identify problems with software systems and solving some of security issues. A log file is a computer-generated data file which provides information on use patterns, activities, and processes occurring within an operating system, application, server, or other devices. The traditional manual log inspection and analysis became impractical and almost impossible due logs’ nature as unstructured, to address this challenge, Machine Learning (ML) is regarded as a reliable solution to analyze log files automatically. This survey tries to explore the existing ML approaches and techniques which are utilized in analyzing log file types. It retrieves and presents the existing relevant studies from different scholar databases, then delivers a detailed comparison among them. It also thoroughly reviews utilized ML techniques in inspecting log files and defines the existing challenges and obstacles for this domain that requires further improvements.https://journals.uhd.edu.iq/index.php/uhdjst/article/view/994log fileslog analysismachine learninganomaly detectionuser behaviorlog file maintenance |
| spellingShingle | Rawand Raouf Abdalla Alaa Khalil Jumaa Log File Analysis Based on Machine Learning: A Survey UHD Journal of Science and Technology log files log analysis machine learning anomaly detection user behavior log file maintenance |
| title | Log File Analysis Based on Machine Learning: A Survey |
| title_full | Log File Analysis Based on Machine Learning: A Survey |
| title_fullStr | Log File Analysis Based on Machine Learning: A Survey |
| title_full_unstemmed | Log File Analysis Based on Machine Learning: A Survey |
| title_short | Log File Analysis Based on Machine Learning: A Survey |
| title_sort | log file analysis based on machine learning a survey |
| topic | log files log analysis machine learning anomaly detection user behavior log file maintenance |
| url | https://journals.uhd.edu.iq/index.php/uhdjst/article/view/994 |
| work_keys_str_mv | AT rawandraoufabdalla logfileanalysisbasedonmachinelearningasurvey AT alaakhaliljumaa logfileanalysisbasedonmachinelearningasurvey |