An ensemble clustering method for intrusion detection

2019 ◽  
Vol 7 (2/3) ◽  
pp. 112
Author(s):  
Kapil K. Wankhade ◽  
Kalpana C. Jondhale
Keyword(s):  
Intrusion Detection ◽  
Ensemble Clustering ◽  
Clustering Method

scholarly journals A new ensemble clustering method based on fuzzy cmeans clustering while maintaining diversity in ensemble

2021 ◽  
Vol 17 (4) ◽  
pp. 103-122
Author(s):  
fatemeh najafi ◽  
hamid parvin ◽  
kamal mirzaei ◽  
samad nejatiyan ◽  
seyede vahideh rezaie ◽  
...  
Keyword(s):  
Ensemble Clustering ◽  
Clustering Method

scholarly journals Entropy clustering-based granular classifiers for network intrusion detection

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Hui Liu ◽  
Gang Hao ◽  
Bin Xing
Keyword(s):  
Support Vector Machine ◽  
Intrusion Detection ◽  
Design Parameters ◽  
Network Intrusion Detection ◽  
Support Vector ◽  
Clustering Method ◽  
Overall Design ◽  
Network Intrusion ◽  
Vector Machines ◽  
Classical Models

AbstractSupport vector machine (SVM) is one of the effective classifiers in the field of network intrusion detection; however, some important information related to classification might be lost in the reprocessing. In this paper, we propose a granular classifier based on entropy clustering method and support vector machine to overcome this limitation. The overall design of classifier is realized with the aid of if-then rules that consists of a premise part and conclusion part. The premise part realized by the entropy clustering method is used here to address the problem of a possible curse of dimensionality, while the conclusion part realized by support vector machines is utilized to build local models. In contrast to the conventional SVM, the proposed entropy clustering-based granular classifiers (ECGC) can be regarded as an entropy-based support function machine. Moreover, an opposition-based genetic algorithm is proposed to optimize the design parameters of the granular classifiers. Experimental results show the effectiveness of the ECGC when compared with some classical models reported in the literatures.

A genetic clustering method for intrusion detection

2004 ◽  
Vol 37 (5) ◽  
pp. 927-942 ◽  
Author(s):  
Yongguo Liu ◽  
Kefei Chen ◽  
Xiaofeng Liao ◽  
Wei Zhang
Keyword(s):  
Intrusion Detection ◽  
Clustering Method ◽  
Genetic Clustering
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