Mapping the Internet: Geolocating Routers by Using Machine Learning

A. Prieditis, Gang Chen
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引用次数: 6

Abstract

Knowing the geolocation of a router can help to predict the geolocation of an Internet user, which is important for local advertising, fraud detection, and geo-fencing applications. For example, the geolocation of the last router on the path to a user is a reasonable guess for the user's geolocation. Current methods for geolocating a router are based on parsing a router's name to find geographic hints. Unfortunately, these methods are noisy and often provide no hints. This paper presents results on using machine learning methods to "sharpen" a router's noisy location based on the time delay between one or more routers and a target router or end user IP address. The novelty of this approach is that geolocation of the one or more routers is not required to be known.
映射互联网:使用机器学习定位路由器
了解路由器的地理位置可以帮助预测Internet用户的地理位置,这对于本地广告、欺诈检测和地理围栏应用程序非常重要。例如,用户路径上的最后一个路由器的地理位置是对用户地理位置的合理猜测。当前对路由器进行地理定位的方法是基于解析路由器的名称来查找地理提示。不幸的是,这些方法是嘈杂的,通常不提供提示。本文展示了使用机器学习方法基于一个或多个路由器与目标路由器或最终用户IP地址之间的时间延迟来“锐化”路由器的噪声位置的结果。这种方法的新颖之处在于不需要知道一个或多个路由器的地理位置。
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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