User characteristics that influence judgment of social engineering attacks in social networks
| Autor: | George R. S. Weir, Samar Muslah Albladi |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Deception
General Computer Science Exploit Computer science media_common.quotation_subject Internet privacy 02 engineering and technology Phishing lcsh:QA75.5-76.95 QA76 020204 information systems Perception lcsh:Information theory 0202 electrical engineering electronic engineering information engineering Social engineering Sophistication media_common Social network Information security business.industry Social engineering (security) lcsh:Q350-390 020201 artificial intelligence & image processing lcsh:Electronic computers. Computer science business |
| Zdroj: | Human-Centric Computing and Information Sciences, Vol 8, Iss 1, Pp 1-24 (2018) Human-centric Computing and Information Sciences |
| ISSN: | 2192-1962 |
| Popis: | Social engineering is a growing source of information security concern. Exploits appear to evolve, with increasing levels of sophistication, in order to target multiple victims. Despite increased concern with this risk, there has been little research activity focused upon social engineering in the potentially rich hunting ground of social networks. In this setting, factors that influence users’ proficiency in threat detection need to be understood if we are to build a profile of susceptible users, develop suitable advice and training programs, and generally help address this issue for those individuals most likely to become targets of social engineering in social networks. To this end, the present study proposes and validates a user-centric framework based on four perspectives: socio-psychological, habitual, socio-emotional, and perceptual. Previous research tends to rely on selected aspects of these perspectives and has not combined them into a single model for a more cohesive understanding of user’s susceptibility. |
| Databáze: | OpenAIRE |
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