DocumentCode
189034
Title
Security Related Data Mining
Author
Monshizadeh, Mehrnoosh ; Zheng Yan
Author_Institution
Finland Dept. of Comnet, Aalto Univ., Espoo, Finland
fYear
2014
fDate
11-13 Sept. 2014
Firstpage
775
Lastpage
782
Abstract
Data mining is the process that extracts, classifies and analyzes valid and useful information from large volumes of data provided by multiple sources. The data mining has been widely applied into various areas, one of which is to investigate potential security threats. In the literature, various data mining techniques such as classification and clustering have been proposed to detect intrusions, DoS attacks, and malware. This paper surveys different data mining techniques applied to detect security threats and analyzes their advantages and disadvantages. Through comparison, we discuss open research issues about security-related data mining and propose future research focus.
Keywords
data analysis; data mining; security of data; DoS attack detection; classification technique; clustering technique; denial-of-service attack; information analysis; information classification; information extraction; intrusion detection; malware detection; security related data mining; security threats; Artificial neural networks; Classification algorithms; Clustering algorithms; Computers; Data mining; Decision trees; Security; Botnet; Data mining; DoS; classification; clustering; intrusion;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer and Information Technology (CIT), 2014 IEEE International Conference on
Conference_Location
Xi´an
Type
conf
DOI
10.1109/CIT.2014.130
Filename
6984750
Link To Document