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A new method to classify malicious domain name using neutrosophic sets in DGA botnet detection.

Authors :
Van Can, Nguyen
Tu, Doan Ngoc
Tuan, Tong Anh
Long, Hoang Viet
Son, Le Hoang
Son, Nguyen Thi Kim
Source :
Journal of Intelligent & Fuzzy Systems. 2020, Vol. 38 Issue 4, p4223-4236. 14p.
Publication Year :
2020

Abstract

In Botnet Detection, Domain generation algorithms are the most effective method to intercept and analyze captured package. In this article, we propose a new method to classify harmful domain names using Neutrosophic Sets. Data of domain name, after being selected featured and fuzzed into Neutrosophic Sets will be used to classify benign domain names, malicious domain names and indeterminacy domain names, minimizing false detection of benign domain names. The proposed model is going to be tested and evaluated with other malicious domain detection models in the aspects of accuracy points, Accuracy, Revocation, and F1, all of which show that our proposed model has good results. [ABSTRACT FROM AUTHOR]

Subjects

Subjects :
*REVOCATION
*ALGORITHMS
*PACKAGING

Details

Language :
English
ISSN :
10641246
Volume :
38
Issue :
4
Database :
Academic Search Index
Journal :
Journal of Intelligent & Fuzzy Systems
Publication Type :
Academic Journal
Accession number :
143006131
Full Text :
https://doi.org/10.3233/JIFS-190681