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DOI: 10.14569/IJACSA.2020.0110119
PDF

Malicious URL Detection based on Machine Learning

Author 1: Cho Do Xuan
Author 2: Hoa Dinh Nguyen
Author 3: Tisenko Victor Nikolaevich

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 11 Issue 1, 2020.

  • Abstract and Keywords
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Abstract: Currently, the risk of network information insecurity is increasing rapidly in number and level of danger. The methods mostly used by hackers today is to attack end-to-end technology and exploit human vulnerabilities. These techniques include social engineering, phishing, pharming, etc. One of the steps in conducting these attacks is to deceive users with malicious Uniform Resource Locators (URLs). As a results, malicious URL detection is of great interest nowadays. There have been several scientific studies showing a number of methods to detect malicious URLs based on machine learning and deep learning techniques. In this paper, we propose a malicious URL detection method using machine learning techniques based on our proposed URL behaviors and attributes. Moreover, bigdata technology is also exploited to improve the capability of detection malicious URLs based on abnormal behaviors. In short, the proposed detection system consists of a new set of URLs features and behaviors, a machine learning algorithm, and a bigdata technology. The experimental results show that the proposed URL attributes and behavior can help improve the ability to detect malicious URL significantly. This is suggested that the proposed system may be considered as an optimized and friendly used solution for malicious URL detection.

Keywords: URL; malicious URL detection; feature extraction; feature selection; machine learning

Cho Do Xuan, Hoa Dinh Nguyen and Tisenko Victor Nikolaevich, “Malicious URL Detection based on Machine Learning” International Journal of Advanced Computer Science and Applications(IJACSA), 11(1), 2020. http://dx.doi.org/10.14569/IJACSA.2020.0110119

@article{Xuan2020,
title = {Malicious URL Detection based on Machine Learning},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2020.0110119},
url = {http://dx.doi.org/10.14569/IJACSA.2020.0110119},
year = {2020},
publisher = {The Science and Information Organization},
volume = {11},
number = {1},
author = {Cho Do Xuan and Hoa Dinh Nguyen and Tisenko Victor Nikolaevich}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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