Detection of Anonymising Proxies Using Machine Learning

IF 0.6 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Shane Miller, K. Curran, T. Lunney
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引用次数: 4

Abstract

Network Proxies and Virtual Private Networks (VPN) are tools that are used every day to facilitate various business functions. However, they have gained popularity amongst unintended userbases as tools that can be used to hide mask identities while using websites and web-services. Anonymising Proxies and/or VPNs act as an intermediary between a user and a web server with a Proxy and/or VPN IP address taking the place of the user’s IP address that is forwarded to the web server. This paper presents computational models based on intelligent machine learning techniques to address the limitations currently experienced by unauthorised user detection systems. A model to detect usage of anonymising proxies was developed using a Multi-layered perceptron neural network that was trained using data found in the Transmission Control Protocol (TCP) header of captured network packets
使用机器学习检测匿名代理
网络代理和虚拟专用网(VPN)是日常使用的工具,用于促进各种业务功能。然而,它们已经在意想不到的用户群中流行起来,作为在使用网站和网络服务时隐藏掩码身份的工具。匿名代理和/或VPN充当用户和web服务器之间的中介,代理和/或VPN IP地址代替用户转发给web服务器的IP地址。本文提出了基于智能机器学习技术的计算模型,以解决当前未经授权的用户检测系统所遇到的限制。使用多层感知器神经网络开发了一个检测匿名代理使用的模型,该网络使用捕获的网络数据包的传输控制协议(TCP)报头中的数据进行训练
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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