The detection of unauthorised users can be problematic for techniques that are available at present if the nefarious actors are using identity hiding tools such as anonymising proxies or Virtual Private Networks (VPNs). This work presents computational models to address the limitations currently experienced in detecting VPN traffic. The experiments conducted to classify OpenVPN usage found that the Neural Network was able to correctly identify the VPN traffic with an overall accuracy of 93.71%. These results demonstrate a significant advancement in the detection of unauthorised user access with evidence showing that there could be further advances for research in this field particularly in the application of business security where the detection of VPN usage is important to an organization.
|Number of pages||20|
|Journal||International Journal of Digital Crime and Forensics|
|Publication status||Accepted/In press - 24 Feb 2021|
- Anonymous proxies
- machine learning
- virtual private networks