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Multi-layered graph-based model for social engineering vulnerability assessment

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Published:25 August 2015Publication History

ABSTRACT

As technological and operational security measures for the protection of information systems are being widely adopted, it is much easier for a malicious user to launch an attack on an information system's weakest link, the humans operating it. Despite the damage that these attacks can cause, they are rarely taken into account in vulnerability assessment models. These models usually focus on representing the internal states of an information system, whereas social engineering attacks often start by gathering information and building relationships with the potential victims, which tends to occur outside an information system's gates. Hence, a model assessing social engineering threats should be able to account for the different channels which could be used to approach victims (professional mail, personnel mail, on-line social networks, etc). Although security professionals might not monitor some of the channels leveraged in an attack, a comprehensive vulnerability assessment model would allow the assessment of the likelihood and cost of a successful breach and tailor a security awareness programs to avoid it. We describe in this paper a multi-layered graph-based model for social engineering vulnerability assessment. We then present case studies in which vulnerabilities in an automated social engineering attack and an automated reverse social engineering attack in addition to vulnerabilities from interactions in different social networking sites, blogs and forums are assessed using this model.

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  1. Multi-layered graph-based model for social engineering vulnerability assessment

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      • Published in

        cover image ACM Conferences
        ASONAM '15: Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2015
        August 2015
        835 pages
        ISBN:9781450338547
        DOI:10.1145/2808797

        Copyright © 2015 ACM

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        Publication History

        • Published: 25 August 2015

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