Clustering based intrusion detection for network profiling using k-means and k-nearest neighbor algorithms

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Clustering based intrusion detection for network profiling using k-means and k-nearest neighbor algorithms

Chairunnisa - Personal Name; Lukas - Personal Name;

Network profiling can be determined using clustering and classification. Clustering groups the intrusion data based on their type. Clustering algorithms that are used in this research are K-means and Evolving Clustering Method (ECM). Comparing the performance of those algorithms for overlapping data that used in this experiment. Classification also need to compare the misclassification from the clusters that created from K-means and ECM algorithms. K-nearest neighbor used in this research for classification.

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B00525 (wh) Available

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Series Title: -
Call Number: 525
Publisher: : Swiss German University., 2009
Collation: -
Language: English
ISBN/ISSN: -
Classification: NONE
Content Type: -
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Edition: -
Subject(s): IT
Specific Detail Info: -
Statement of Responsibility: -

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