Two state-based approaches to program-based anomaly detection

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	Similar Articles Articles by C.C. Michael Articles by A. Ghosh

16th Annual Computer Security Applications Conference (ACSAC'00)

New Orleans, Louisiana

December 11-December 15

ISBN: 0-7695-0859-6

	ASCII Text	x
	C.C. Michael, A. Ghosh, "Two state-based approaches to program-based anomaly detection," Computer Security Applications Conference, Annual, pp. 21, 16th Annual Computer Security Applications Conference (ACSAC'00), 2000.

	BibTex	x
	@article{ 10.1109/ACSAC.2000.898854, author = {C.C. Michael and A. Ghosh}, title = {Two state-based approaches to program-based anomaly detection}, journal ={Computer Security Applications Conference, Annual}, volume = {0}, year = {2000}, issn = {1063-9527}, pages = {21}, doi = {http://doi.ieeecomputersociety.org/10.1109/ACSAC.2000.898854}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Computer Security Applications Conference, Annual TI - Two state-based approaches to program-based anomaly detection SN - 1063-9527 SP EP A1 - C.C. Michael, A1 - A. Ghosh, PY - 2000 KW - security of data; software performance evaluation; auditing; finite state machines; state-based approaches; program-based anomaly detection; intrusion detection algorithms; experimental results; algorithm performance; execution audit data; finite-state machine; statistical deviation monitoring; n-grams VL - 0 JA - Computer Security Applications Conference, Annual ER -

C.C. Michael, RST Res. Labs., USA

A. Ghosh, RST Res. Labs., USA

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ACSAC.2000.898854

This paper describes two intrusion detection algorithms, and gives experimental results on their performance. The algorithms detect anomalies in execution audit data. One is a simply constructed finite-state machine, and the other monitors statistical deviations from normal program behavior. The performance of these algorithms is evaluated as a function of the amount of available training data, and they are compared to the well-known intrusion detection technique of looking for novel n-grams in computer audit data.

Index Terms:

security of data; software performance evaluation; auditing; finite state machines; state-based approaches; program-based anomaly detection; intrusion detection algorithms; experimental results; algorithm performance; execution audit data; finite-state machine; statistical deviation monitoring; n-grams

Citation:

C.C. Michael, A. Ghosh, "Two state-based approaches to program-based anomaly detection," acsac, pp.21, 16th Annual Computer Security Applications Conference (ACSAC'00), 2000

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