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Article type: Research Article
Authors: Van Can, Nguyena | Tu, Doan Ngoca | Tuan, Tong Anha | Long, Hoang Vieta | Son, Le Hoangb | Son, Nguyen Thi Kimc; d; *
Affiliations: [a] Facutly of Information Technology, People’s Police University of Technology and Logistics, Bac Ninh, Vietnam | [b] VNU Information Technology Institute, Vietnam National University, Hanoi, Vietnam | [c] Division of Computational Mathematics and Engineering, Institute for Computational Science, Ton Duc Thang University, Ho Chi Minh City, Vietnam | [d] Faculty of Mathematics and Statistics, Ton Duc Thang University, Ho Chi Minh City, Vietnam
Correspondence: [*] Corresponding author. Nguyen Thi Kim Son, E-mail: nguyenthikimson@tdtu.edu.vn.
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.
Keywords: DGA domain detection, neutrosophic clustering, classifying
DOI: 10.3233/JIFS-190681
Journal: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 4, pp. 4223-4236, 2020
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