Efficient Event Log Mining with LogClusterC

被引:4
作者
Chen Zhuge [1 ]
Vaarandi, Risto [1 ]
机构
[1] Tallinn Univ Technol, TUT Ctr Digital Forens & Cyber Secur, Tallinn, Estonia
来源
2017 IEEE 3RD INTERNATIONAL CONFERENCE ON BIG DATA SECURITY ON CLOUD (BIGDATASECURITY, IEEE 3RD INTERNATIONAL CONFERENCE ON HIGH PERFORMANCE AND SMART COMPUTING, (HPSC) AND 2ND IEEE INTERNATIONAL CONFERENCE ON INTELLIGENT DATA AND SECURITY (IDS) | 2017年
关键词
event log clustering; mining line patterns from event logs; LogCluster algorithm; data clustering; data mining;
D O I
10.1109/BigDataSecurity.2017.26
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Nowadays, many organizations collect large volumes of event log data on a daily basis, and the analysis of collected data is a challenging task. For this purpose, data mining methods have been suggested in past research papers, and several data clustering algorithms have been developed for mining line patterns from event logs. In this paper, we introduce an open-source tool called LogClusterC which implements the LogCluster algorithm for discovering line patterns and outliers from event logs. According to our performance measurements, LogClusterC compares favorably to other publicly available log clustering tools.
引用
收藏
页码:261 / 266
页数:6
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