Journal ArticleDOI
ADAM: a testbed for exploring the use of data mining in intrusion detection
Daniel Barbará,Julia Couto,Sushil Jajodia,Ningning Wu +3 more
- Vol. 30, Iss: 4, pp 15-24
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TLDR
The design and experiences with the ADAM (Audit Data Analysis and Mining) system are described, which is used as a testbed to study how useful data mining techniques can be in intrusion detection.Abstract:
Intrusion detection systems have traditionally been based on the characterization of an attack and the tracking of the activity on the system to see if it matches that characterization. Recently, new intrusion detection systems based on data mining are making their appearance in the field. This paper describes the design and experiences with the ADAM (Audit Data Analysis and Mining) system, which we use as a testbed to study how useful data mining techniques can be in intrusion detection.read more
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TL;DR: This paper provides a comprehensive survey of anomaly detection systems and hybrid intrusion detection systems of the recent past and present and discusses recent technological trends in anomaly detection and identifies open problems and challenges in this area.
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References
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Journal ArticleDOI
Data mining: practical machine learning tools and techniques with Java implementations
Ian H. Witten,Eibe Frank +1 more
TL;DR: This presentation discusses the design and implementation of machine learning algorithms in Java, as well as some of the techniques used to develop and implement these algorithms.
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Outliers in Statistical Data
Vic Barnett,Toby Lewis +1 more
TL;DR: In this article, the authors present an updated version of the reference work on outliers, including new areas of study such as outliers in direction data as well as developments in fields such as discordancy tests for univariate and multivariate samples.