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Anomaly Detection for System Log Analysis using Machine Learning: Recent Approaches, Challenges and Opportunities in Network Forensics

Anomaly detection identifies unusual patterns or items in a dataset. The anomalies identified for system logs will signify critical points to help debug system failures and perform root cause analysis. Various system logs are crucial sources to uncover meaningful information on a system condition. T...

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Bibliographic Details
Main Authors: Farashazillah Yahya, Nurul Huda Nik Zulkifli, Hasimi Sallehudin, Nur Azaliah Abu Bakar
Format: Article
Language:English
English
Published: 2020
Subjects:
Q Science (General)
QA Mathematics
Online Access:https://eprints.ums.edu.my/id/eprint/26318/1/Anomaly%20Detection%20for%20System%20Log%20Analysis%20using%20Machine%20Learning%20Recent%20Approaches%2C%20Challenges%20and%20Opportunities%20in%20Network%20Forensics.pdf
https://eprints.ums.edu.my/id/eprint/26318/2/Anomaly%20Detection%20for%20System%20Log%20Analysis%20using%20Machine%20Learning%20Recent%20Approaches%2C%20Challenges%20and%20Opportunities%20in%20Network%20Forensics.pdf
https://eprints.ums.edu.my/id/eprint/26318/
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https://eprints.ums.edu.my/id/eprint/26318/1/Anomaly%20Detection%20for%20System%20Log%20Analysis%20using%20Machine%20Learning%20Recent%20Approaches%2C%20Challenges%20and%20Opportunities%20in%20Network%20Forensics.pdf
https://eprints.ums.edu.my/id/eprint/26318/2/Anomaly%20Detection%20for%20System%20Log%20Analysis%20using%20Machine%20Learning%20Recent%20Approaches%2C%20Challenges%20and%20Opportunities%20in%20Network%20Forensics.pdf
https://eprints.ums.edu.my/id/eprint/26318/

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