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- W2887579214 abstract "Social networking sites often witness various types of social engineering (SE) attacks. Yet, limited research has addressed the most severe types of social engineering in social networks (SNs). The present study investigates the extent to which people respond differently to different types of attack in a social network context and how we can segment users based on their vulnerability. In turn, this leads to the prospect of a personalised security advisory system. 316 participants have completed an online-questionnaire that includes a scenario-based experiment. The study result reveals that people respond to cyber-attacks differently based on their demographics. Furthermore, people’s competence, social network experience, and their limited connections with strangers in social networks can decrease their likelihood of falling victim to some types of attacks more than others." @default.
- W2887579214 created "2018-08-22" @default.
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- W2887579214 date "2018-01-01" @default.
- W2887579214 modified "2023-09-25" @default.
- W2887579214 title "A Semi-automated Security Advisory System to Resist Cyber-Attack in Social Networks" @default.
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- W2887579214 doi "https://doi.org/10.1007/978-3-319-98443-8_14" @default.
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