Journal ArticleDOI
The KDD process for extracting useful knowledge from volumes of data
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This article is published in Communications of The ACM.The article was published on 1996-11-01. It has received 1857 citations till now. The article focuses on the topics: Knowledge extraction.read more
Citations
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Journal ArticleDOI
Anomaly-based network intrusion detection: Techniques, systems and challenges
TL;DR: The main challenges to be dealt with for the wide scale deployment of anomaly-based intrusion detectors, with special emphasis on assessment issues are outlined.
Journal ArticleDOI
A Survey of Data Mining and Machine Learning Methods for Cyber Security Intrusion Detection
Anna L. Buczak,Erhan Guven +1 more
TL;DR: The complexity of ML/DM algorithms is addressed, discussion of challenges for using ML/ DM for cyber security is presented, and some recommendations on when to use a given method are provided.
ReportDOI
Data mining approaches for intrusion detection
Wenke Lee,Salvatore J. Stolfo +1 more
TL;DR: An agent-based architecture for intrusion detection systems where the learning agents continuously compute and provide the updated (detection) models to the detection agents is proposed.
Proceedings ArticleDOI
A data mining framework for building intrusion detection models
TL;DR: A data mining framework for adaptively building Intrusion Detection (ID) models is described, to utilize auditing programs to extract an extensive set of features that describe each network connection or host session, and apply data mining programs to learn rules that accurately capture the behavior of intrusions and normal activities.
Proceedings Article
New algorithms for fast discovery of association rules
TL;DR: New algorithms for fast association mining, which scan the database only once, are presented, addressing the open question whether all the rules can be efficiently extracted in a single database pass.
References
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Journal ArticleDOI
Applications of machine learning and rule induction
Pat Langley,Herbert A. Simon +1 more
TL;DR: This paper aims to provide increasing levels of automation in the knowledge engineering process, replacing much time-consuming human activity with automatic techniques that improve accuracy or efficiency by discovering and exploiting regularities in training data.
Proceedings Article
A statistical perspective on KDD
John Elder,Daryl Pregibon +1 more
TL;DR: Some major advances in statistics from recent decades that are applicable to Knowledge Discovery in Databases are reviewed.