DocumentCode
2780516
Title
Taxonomy of statistical based anomaly detection techniques for intrusion detection
Author
Qayyum, A. ; Islam, M.H. ; Jamil, M.
fYear
2005
fDate
17-18 Sept. 2005
Firstpage
270
Lastpage
276
Abstract
Security threats to the computer systems have raised the importance of intrusion detection systems. With the advent of new vulnerabilities to computer systems new techniques for intrusion detection have been implemented. Statistical based anomaly detection techniques use statistical properties and statistical tests to determine whether "observed behavior" deviate significantly from the "expected behavior". Statistical based anomaly detection has been a wide area of interest for researchers since it provides the base line for developing a promising technique. This paper presents a guideline for statistical based anomaly detection techniques with the perspective of various scenarios and areas of implementation.
Keywords
computer networks; security of data; statistical analysis; computer systems; intrusion detection; intrusion detection systems; statistical based anomaly detection technique taxonomy; statistical properties; Computer aided software engineering; Computer crime; Computer networks; Computer security; Computer viruses; Guidelines; Intrusion detection; Statistical analysis; Taxonomy; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Emerging Technologies, 2005. Proceedings of the IEEE Symposium on
Print_ISBN
0-7803-9247-7
Type
conf
DOI
10.1109/ICET.2005.1558893
Filename
1558893
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