A new method to classify malicious domain name using neutrosophic sets in DGA botnet detection
Nguyen Van Can, Doan Ngoc Tu, Tong Anh Tuan, Hoang Viet Long, Lê Hoàng Sơn, Nguyen Thi Kim Son
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.