Detection Technique to trace IP behind VPN/Proxy using Machine Learning

D. Naidu, Madhav Jha
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引用次数: 0

Abstract

Cybercriminals use a variation of techniques to fleece their digital footprints, that creates a barrier for law enforcement agencies to impossibly catch and prosecute them. With the known universal truth that whenever a machine tries to connect in adversely to target system. The victim’s machine can see only requests coming from the “proxy” or the VPN server. Now as VPN hides IP addresses it leads the network to be redirected through some special configured remote server which are run by a VPN host. As its consequences, the user’s digital footprint is hidden. the footprint of a VPN server is received by the receiver. This challenges the entire organization or one’s personal system to be in risk. One such solution to the problem is to design “Honeypot system” that will trace an IP address running behind VPN/proxy servers. The machine learning algorithm will able to trace the actual IP address with ISP details. The paper discusses a detection mechanism that will dupe the attackers. Showing inability in locating and identifying real honeypot file. The methods were tested on various platforms and technique outperform in detecting attacker’s system smartly using machine learning.
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使用机器学习跟踪VPN/代理背后IP的检测技术
网络犯罪分子使用各种各样的技术来清除他们的数字足迹,这给执法机构创造了一个不可能抓住和起诉他们的障碍。众所周知,每当一台机器试图恶意连接到目标系统时。受害者的机器只能看到来自“代理”或VPN服务器的请求。现在,由于VPN隐藏了IP地址,它导致网络通过一些由VPN主机运行的特殊配置的远程服务器进行重定向。其结果是,用户的数字足迹是隐藏的。VPN服务器的足迹被接收方接收。这会使整个组织或个人系统处于危险之中。一个这样的解决方案是设计“蜜罐系统”,它将跟踪VPN/代理服务器后面运行的IP地址。机器学习算法将能够通过ISP详细信息跟踪实际IP地址。本文讨论了一种能够欺骗攻击者的检测机制。显示无法定位和识别真正的蜜罐文件。这些方法在各种平台上进行了测试,并且在使用机器学习智能检测攻击者系统方面表现出色。
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来源期刊
International Journal of Next-Generation Computing
International Journal of Next-Generation Computing COMPUTER SCIENCE, THEORY & METHODS-
自引率
66.70%
发文量
60
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