DocumentCode
2723933
Title
Applying Data Mining Techniques to Intrusion Detection
Author
Ng, Jonathon ; Joshi, Deepti ; Banik, Shankar M.
Author_Institution
Dept. of Math. & Comput. Sci., Citadel, Charleston, SC, USA
fYear
2015
fDate
13-15 April 2015
Firstpage
800
Lastpage
801
Abstract
In our current society, the threat of cyber intrusion is increasingly high and harmful. With the rise of usage in computers, criminal activity has also shifted from physical intrusion into cyber intrusion. Intrusion detection systems provide the ability to identify security breaches in a system. A security breach will be any action the owner of the system deems unauthorized. Current methods used for these systems include using anomaly detection or a signature database. In this research we use both anomaly detection and a signature database using data mining techniques. Our solution provides a tool that would run data mining tools against a log file to detect patterns that may be considered an unauthorized activity. The tool gains additional patterns as time goes by and grows more effective. It allowed us to detect brute force password cracking and Denial-of-Service (DoS) attacks on a system in the Ubuntu platform.
Keywords
Linux; computer network security; data mining; digital signatures; Ubuntu platform; anomaly detection; brute force password cracking detection; criminal activity; cyber intrusion threat; data mining techniques; denial-of-service attacks detection; intrusion detection systems; pattern detection; physical intrusion; security breach identification; signature database; Computer crime; Computers; Data mining; Databases; Intrusion detection; Servers; Cybersecurity; Data Mining; Intrusion Detection;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Technology - New Generations (ITNG), 2015 12th International Conference on
Conference_Location
Las Vegas, NV
Print_ISBN
978-1-4799-8827-3
Type
conf
DOI
10.1109/ITNG.2015.146
Filename
7113585
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