• DocumentCode
    2359355
  • Title

    Social engineering attack detection model: SEADM

  • Author

    Bezuidenhout, Monique ; Mouton, Francois ; Venter, H.S.

  • Author_Institution
    Dept. of Psychol., Univ. of Pretoria, Pretoria, South Africa
  • fYear
    2010
  • fDate
    2-4 Aug. 2010
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    Social engineering is a real threat to industries in this day and age even though the severity of it is extremely downplayed. The difficulty with social engineering attacks is mostly the ability to identify them. Social engineers target call centre employees, as they are normally underpaid, under skilled workers whom have limited knowledge about the information technology infrastructure. These workers are thus easy targets for the social engineer. This paper proposes a model which can be used by these workers to detect social engineering attacks in a call centre environment. The model is a quick and effective way to determine if the requester is trying to manipulate an individual into disclosing information to which the requester does not have authorization for.
  • Keywords
    authorisation; call centres; personnel; authorization; call centre employee; information technology infrastructure; social engineering attack detection model; Biological system modeling; Cognition; Computational modeling; Decision making; Humans; Psychology; Utility theory; Social engineering; emotional state; information sensitivity; social psychology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Security for South Africa (ISSA), 2010
  • Conference_Location
    Sandton, Johannesburg
  • Print_ISBN
    978-1-4244-5493-8
  • Type

    conf

  • DOI
    10.1109/ISSA.2010.5588500
  • Filename
    5588500