A supervised clustering algorithm for computer intrusion detection

Xiangyang Li; Nong Ye

doi:10.1007/s10115-005-0195-8

A supervised clustering algorithm for computer intrusion detection

Xiangyang Li, Nong Ye

Industrial, Systems and Operations Engineering

Research output: Contribution to journal › Article › peer-review

13 Scopus citations

Abstract

We previously developed a clustering and classification algorithm - supervised (CCAS) to learn patterns of normal and intrusive activities and to classify observed system activities. Here we further enhance the robustness of CCAS to the presentation order of training data and the noises in training data. This robust CCAS adds data redistribution, a supervised hierarchical grouping of clusters and removal of outliers as the postprocessing steps.

Original language	English (US)
Pages (from-to)	498-509
Number of pages	12
Journal	Knowledge and Information Systems
Volume	8
Issue number	4
DOIs	https://doi.org/10.1007/s10115-005-0195-8
State	Published - Nov 2005

Keywords

Classification
Clustering
Intrusion detection

ASJC Scopus subject areas

Software
Information Systems
Human-Computer Interaction
Hardware and Architecture
Artificial Intelligence

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10.1007/s10115-005-0195-8

Cite this

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title = "A supervised clustering algorithm for computer intrusion detection",

abstract = "We previously developed a clustering and classification algorithm - supervised (CCAS) to learn patterns of normal and intrusive activities and to classify observed system activities. Here we further enhance the robustness of CCAS to the presentation order of training data and the noises in training data. This robust CCAS adds data redistribution, a supervised hierarchical grouping of clusters and removal of outliers as the postprocessing steps.",

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AU - Ye, Nong

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AB - We previously developed a clustering and classification algorithm - supervised (CCAS) to learn patterns of normal and intrusive activities and to classify observed system activities. Here we further enhance the robustness of CCAS to the presentation order of training data and the noises in training data. This robust CCAS adds data redistribution, a supervised hierarchical grouping of clusters and removal of outliers as the postprocessing steps.

KW - Classification

KW - Clustering

KW - Intrusion detection

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JF - Knowledge and Information Systems

IS - 4

ER -

A supervised clustering algorithm for computer intrusion detection

Abstract

Keywords

ASJC Scopus subject areas

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