DocumentCode :
3517622
Title :
Empirical Evaluation of the Internet Analysis System for Application in the Field of Anomaly Detection
Author :
Lampesberger, Harald
Author_Institution :
Dept. Secure Inf. Syst., Upper Austria Univ. of Appl. Sci., Linz, Austria
fYear :
2010
fDate :
28-29 Oct. 2010
Firstpage :
63
Lastpage :
70
Abstract :
Anomaly detection in computer networks is an actively researched topic in the field of intrusion detection. The Internet Analysis System (IAS) is a software framework which provides passive probes and centralized backend services to collect purely statistical network data in distributed computer networks. This paper presents an empirical evaluation of the IAS data format for detecting anomalies, caused by attack traffic. This process involved the generation of labeled evaluation data based on the 1999 DARPA Intrusion Detection Evaluation data sets and two different supervised machine learning approaches for the assessment. The results of this evaluation conclude, that the IAS is not a convenient data source for advanced anomaly detection in the scope of our research.
Keywords :
Internet; computer network security; learning (artificial intelligence); 1999 DARPA intrusion detection evaluation; IAS data format; Internet analysis system; anomaly detection; centralized backend service; convenient data source; distributed computer network; labeled evaluation data; software framework; statistical network data; supervised machine learning approach; Context; Internet; Intrusion detection; Probes; Testing; Training; evaluation data; intrusion detection; machine learning; supervised anomaly detection;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Network Defense (EC2ND), 2010 European Conference on
Conference_Location :
Berlin
Print_ISBN :
978-1-4244-9377-7
Type :
conf
DOI :
10.1109/EC2ND.2010.10
Filename :
5663318
Link To Document :
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