Journal ArticleDOI
A data reduction method for intrusion detection
TLDR
A data reduction method is presented that makes multivariate data analysis involved in intrusion detection more efficient and extracts, from the original data set, discriminating components that best characterize user behavior.About:
This article is published in Journal of Systems and Software.The article was published on 1996-04-01. It has received 20 citations till now. The article focuses on the topics: Anomaly-based intrusion detection system & Intrusion detection system.read more
Citations
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Journal ArticleDOI
Application of SVM and ANN for intrusion detection
TL;DR: Two data mining methodologies-Artificial Neural Networks and Support Vector Machine and two encoding methods-simple frequency-based scheme and tfi?idf scheme are used to detect potential system intrusions in this study.
Proceedings ArticleDOI
Fuzzy network profiling for intrusion detection
TL;DR: This paper describes the components in the FIRE architecture and explains their roles, with particular attention given to explaining the benefits of data mining and how this can improve the meaningfulness of the fuzzy sets.
Proceedings ArticleDOI
Fuzzy intrusion detection
TL;DR: The Fuzzy Intrusion Recognition Engine (FIRE) is a network intrusion detection system that uses fuzzy systems to assess malicious activity against computer networks and can be effective at detecting some types of backdoor and Trojan horse attacks.
Journal ArticleDOI
The neural network models for IDS based on the asymmetric costs of false negative errors and false positive errors
TL;DR: The results of the empirical experiment and the simulation results show that the effectiveness of intrusion detection can be enhanced by considering the asymmetric costs of false negative and false positive errors.
Book ChapterDOI
Data Mining for Intrusion Detection
TL;DR: This chapter surveys a representative cross section of research projects that have applied data mining to various problems in intrusion detection over the past five years.
References
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Journal ArticleDOI
An Intrusion-Detection Model
TL;DR: A model of a real-time intrusion-detection expert system capable of detecting break-ins, penetrations, and other forms of computer abuse is described, based on the hypothesis that security violations can be detected by monitoring a system's audit records for abnormal patterns of system usage.
Journal ArticleDOI
Graph-Theoretical Methods for Detecting and Describing Gestalt Clusters
TL;DR: A family of graph-theoretical algorithms based on the minimal spanning tree are capable of detecting several kinds of cluster structure in arbitrary point sets; description of the detected clusters is possible in some cases by extensions of the method.
Proceedings ArticleDOI
An Intrusion-Detection Model
TL;DR: A model of a real-time intrusion-detection expert system capable of detecting break-ins, penetrations, and other forms of computer abuse is described, based on the hypothesis that security violations can be detected by monitoring a system's audit records for abnormal patterns of system usage.