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Research on user identification algorithm based on massive multi-site VPN log

机译:基于大规模多站点VPN日志的用户识别算法研究

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摘要

VPN (Virtual Private Network) is the primary mean for users to access network information by crossing the border currently. There is little research about VPN users, though the number of users who using VPN is pretty large. Consequently, it is desiderated to find a solution to strengthen the ability to observe and discover cross-border access users. This paper proposes a novel user identification algorithm according to massive multi-site VPN log. First of all, a formal description of VPN user identification problems is given, then we analyze quantitatively for probability distribution of VPN log in two dimensions: usernames and CIP (Client Internet Protocol) addresses. Based on this, we give the solution of problems in VPN user identification, and propose a user identification algorithm based on the combination of access vector similarity, username similarity, the number of regions where users surf the internet and the connected subgraphs. Then we test the algorithm in VPN log within two months, which has proved the effectiveness and correctness of user identification algorithm.
机译:VPN(虚拟专用网络)是用户当前通过过边界访问网络信息的主要含义。关于VPN用户几乎没有研究,尽管使用VPN的用户数量非常大。因此,可以寻求找到一种解决方案,以加强观察和发现跨境访问用户的能力。本文提出了一种新颖的用户识别算法,根据大规模的多站点VPN日志。首先,给出了VPN用户识别问题的正式描述,然后我们为VPN登录的概率分布定量分析了两个维度:用户名和CIP(客户端Internet协议)地址。基于此,我们提供了在VPN用户识别中的问题的解决方案,并提出了一种基于接入向量相似性,用户名相似性的组合的用户识别算法,用户中浏览因特网的区域和所连接的子图。然后我们在两个月内测试VPN日志中的算法,这已经证明了用户识别算法的有效性和正确性。

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