Localising social network users and profiling their movement

Hector Pellet, Stavros Shiaeles*, Stavros Stavrou

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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Abstract

Open-source intelligence (OSINT) is intelligence collected from publicly available sources to meet specific intelligence requirements. This paper proposes a new method to localise and profile the movement of social network users through OSINT and machine learning techniques. Analysis of obtained OSINT social networks posts data from targeted users, suggests that it is possible to extract information such as their approximate location, leading also to the profiling of their movement, without using any supported Global Navigation Satellite System functionality which may be passed to the social network through a capable smart device. The ability to profile a target's movement activity could allow anyone to track a social network user or predict his or her future location. Moreover, in this work, we also demonstrate that information from social networks can be extracted relatively in real time, thus targeted users are prone to lose any sense of physical privacy.

Original languageEnglish
Pages (from-to)49-57
Number of pages9
JournalComputers and Security
Volume81
Early online date2 Nov 2018
DOIs
Publication statusPublished - 1 Mar 2019

Keywords

  • Facebook
  • Geo-Location
  • Instagram
  • Machine Learning
  • Natural Language Processing
  • OSINT
  • Social Media
  • Twitter

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