• DocumentCode
    3281066
  • Title

    A Method for Identifying Malicious Activity in Collaborative Systems with Maps

  • Author

    Furtado, Vasco ; Assuncao, T. ; de Oliveira, Mauricio ; Belchior, Mairon ; D´Orleans, Jonathan

  • Author_Institution
    Univ. de Fortaleza, Fortaleza, Brazil
  • fYear
    2009
  • fDate
    20-22 July 2009
  • Firstpage
    334
  • Lastpage
    337
  • Abstract
    In this paper we describe the method we have created for the purpose of identifying misbehavior of users who intends to generate false trends in digital maps. Basically, the idea is to identify patterns of communities of users who strongly contribute with reports that lead a particular geographic area to be considered a hot spot. The association between hot spots, computed from Kernel Density Estimation techniques, and the methods for identifying communities in social networks is the main innovation of the method proposed. A multi-agent system was built in order to simulate several scenarios of malicious activities. This method has shown to be effective for alerting the possibility of malicious activity in a real system.
  • Keywords
    groupware; multi-agent systems; security of data; social networking (online); collaborative systems; digital maps; geographic area; kernel density estimation techniques; malicious activity identification; multiagent system; social networks; user community; user misbehavior; Collaboration; Computational modeling; Computer networks; Kernel; Monitoring; Multiagent systems; Smoothing methods; Social network services; Technological innovation; Visualization; colaborative systems; data mining; social networks; wikimapps;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Social Network Analysis and Mining, 2009. ASONAM '09. International Conference on Advances in
  • Conference_Location
    Athens
  • Print_ISBN
    978-0-7695-3689-7
  • Type

    conf

  • DOI
    10.1109/ASONAM.2009.35
  • Filename
    5231843