Research Paper | Computer Science & Engineering | India | Volume 5 Issue 8, August 2016
Enhancing Security and Event Management Using Association Rule Mining
M. Nithya | A. Komathi 
Abstract: Security data and event management system is the industry-specific term to secure the data from the unauthorized one on the collection of knowledge usually log files or event logs from various sources into a central repository for analysis. The design of Security Information and Event Management system and so the rule of algorithm for the correlation analysis. The information flow in and out of the atmosphere, however this information is being accessed, modified, and monitored at totally different points, and the way all the security solutions relate to every alternative in several things. Varied association rules to find normal and abnormal patterns with attack types. Here the system is to calculate the difficulty level to generate the rules by classification and the association rule to mine the abnormal types. The testing dataset is NSL KDD dataset filtered into 4 anomaly class and one normal class. The dataset is processed using WEKA tool.
Keywords: SIEM, NSL-KDD Dataset, Classification Rule, Association Rule, Weka Tool
Edition: Volume 5 Issue 8, August 2016,
Pages: 985 - 990
How to Cite this Article?
M. Nithya, A. Komathi, "Enhancing Security and Event Management Using Association Rule Mining", International Journal of Science and Research (IJSR), Volume 5 Issue 8, August 2016, pp. 985-990, https://www.ijsr.net/get_abstract.php?paper_id=ART2016980
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