• DocumentCode
    3081601
  • Title

    Mapping the Internet: Geolocating Routers by Using Machine Learning

  • Author

    Prieditis, Armand ; Gang Chen

  • Author_Institution
    Neustar Labs., Mountain View, CA, USA
  • fYear
    2013
  • fDate
    22-24 July 2013
  • Firstpage
    101
  • Lastpage
    105
  • 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.
  • Keywords
    Internet; geography; learning (artificial intelligence); Internet; fraud detection; geo-fencing; local advertising; machine learning methods; time delay; Clustering algorithms; Computers; Geology; IP networks; Internet; Noise measurement; Training; Clustering; Geolocation; Machine Learning; Prediction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computing for Geospatial Research and Application (COM.Geo), 2013 Fourth International Conference on
  • Conference_Location
    San Jose, CA
  • Type

    conf

  • DOI
    10.1109/COMGEO.2013.17
  • Filename
    6602048