A Visualization Method Based on Graph Database in Security Logs Analysis

被引：2

作者：

Tang, Xinyu ^{[1
,2
]}

Ma, Chunguang ^{[1
]}

Yu, Min ^{[2
,3
]}

Liu, Chao ^{[2
]}

机构：

[1] Harbin Engn Univ, Coll Comp Sci & Technol, Harbin, Heilongjiang, Peoples R China

[2] Chinese Acad Sci, Inst Informat Engn, Beijing, Peoples R China

[3] Univ Chinese Acad Sci, Sch Cyber Secur, Beijing, Peoples R China

来源：

2017 6TH INTERNATIONAL CONFERENCE ON ADVANCED MATERIALS AND COMPUTER SCIENCE (ICAMCS 2017) | 2017年

基金：

中国国家自然科学基金;

关键词：

Network Forensics; Log Analysis; Association rule mining; Graph Database;

D O I：

10.23977/icamcs.2017.1012

中图分类号：

TH [机械、仪表工业];

学科分类号：

0802 ;

摘要：

Network security logs can provide evidence for forensic investigators. However, the network logs are facing the problems of high repetition rate, high false alarm rate, uniform format and so on, which make it difficult for forensic researchers to find useful information. In this paper, the association rules mining algorithm is used to analyze the network security logs, so as to eliminate the redundant data and to find the implied association between the logs data. Then the graph database is used to visualize the log information. Forensic analysts can obtain effective evidence by observing the graph database, which can improve the efficiency of the forensic analysts to discover the sensitive event information.

引用

页码：82 / 89

页数：8

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