Using Domain-Based on Machine Learning for Malware Detection

Vu, Dai Hoang (2019) Using Domain-Based on Machine Learning for Malware Detection. Masters thesis, Dublin, National College of Ireland.

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Abstract

Cybersecurity attacks are constantly occurring and tend to increase every year. Defensive and preventive measures taken by security experts to protect users are constantly being updated, but attackers are always using more sophisticated techniques. In recent times, many malware has used domain generation algorithms (DGA) to create malicious domains to maintain the C&C infrastructure network (Command and Control). With the use of algorithms from machine learning, we have used approaches from the Logistic Regression, Random Forest and Naïve Bayes algorithms to sort out legitimate domain names and malicious domain names. The result data at the end of the article shows the positive of these methods.

Item Type:	Thesis (Masters)
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science Q Science > QA Mathematics > Computer software T Technology > T Technology (General) > Information Technology > Computer software Q Science > QA Mathematics > Computer software > Computer Security T Technology > T Technology (General) > Information Technology > Computer software > Computer Security
Divisions:	School of Computing > Master of Science in Cyber Security
Depositing User:	Caoimhe Ní Mhaicín
Date Deposited:	02 Apr 2020 11:51
Last Modified:	02 Apr 2020 11:51
URI:	https://norma.ncirl.ie/id/eprint/4161

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