Identifying the Use of Anonymising Proxies to Conceal Source IP Addresses

IF 0.6 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Shane Miller, K. Curran, T. Lunney
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引用次数: 0

Abstract

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.
识别使用匿名代理隐藏源IP地址
如果恶意行为者使用匿名代理或虚拟专用网络(vpn)等身份隐藏工具,那么检测未经授权的用户对于目前可用的技术来说可能会有问题。这项工作提出了计算模型,以解决目前在检测VPN流量方面遇到的限制。对OpenVPN使用情况进行分类的实验发现,神经网络能够正确识别VPN流量,总体准确率为93.71%。这些结果表明,在检测未经授权的用户访问方面取得了重大进展,有证据表明,在这一领域的研究可能会有进一步的进展,特别是在检测VPN使用情况对组织很重要的商业安全应用方面。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
International Journal of Digital Crime and Forensics
International Journal of Digital Crime and Forensics COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-
CiteScore
2.70
自引率
0.00%
发文量
15
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