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 :
بازگشت