Spot the hotspot: Wi-Fi hotspot classification from internet traffic

Andrey Finkelshtein, Rami Puzis, Asaf Shabtai, Bronislav Sidik

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The meteoric progress of Internet technologies and PDA (personal digital assistant) devices has made public Wi-Fi hotspots very popular. Nowadays, hotspots can be found almost anywhere: organizations, home networks, public transport systems, restaurants, etc. The Internet usage patterns (e.g. browsing) differ with the hotspot venue. This insight introduces new traffic profiling opportunities. Using machine learning techniques we show that it is possible to infer types of venues that provide Wi-Fi access (e.g., organizations and hangout places) by analyzing the Internet traffic of connected mobile phones. We show that it is possible to infer the user’s current venue type disclosing his/her current context. This information can be used for improving personalized and context aware services such as web search engines or online shops, without the presence on user’s device. In this paper we evaluate venue type inference based on mobile phone traffic collected from 115 college students and analyze their Internet behavior across the different venues types.

Original languageEnglish
Title of host publicationSocial, Cultural, and Behavioral Modeling - 9th International Conference, SBP-BRiMS 2016, Proceedings
EditorsNathaniel Osgood, Kevin S. Xu, David Reitter, Dongwon Lee
PublisherSpringer Verlag
Pages239-249
Number of pages11
ISBN (Print)9783319399300
DOIs
StatePublished - 1 Jan 2016
Event9th International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction and Behavior Representation in Modeling and Simulation, SBP-BRiMS 2016 - Washington, United States
Duration: 28 Jun 20161 Jul 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9708 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference9th International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction and Behavior Representation in Modeling and Simulation, SBP-BRiMS 2016
Country/TerritoryUnited States
CityWashington
Period28/06/161/07/16

Keywords

  • Classification
  • Hotspot
  • Machine learning
  • Smartphone
  • Wi-Fi

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