Inside the Insider Threats
Permanent URI for this collection
Browse
Recent Submissions
Item Connected Aircraft: Cyber-Safety Risks, Insider Threat, and Management Approaches(2019-01-08) Pollard, Todd; Clark, JasonItem Federated Platooning: Insider Threats and Mitigations(2019-01-08) Callegati, Franco; Giallorenzo, Saverio; Gabbrielli, Maurizio; Melis, Andrea; Prandini, MarcoItem Leader Member Exchange: An Interactive Framework to Uncover a Deceptive Insider as Revealed by Human Sensors(2019-01-08) Ho Ph.D., Shuyuan MaryThis study intends to provide a theoretical ground that conceptualizes the prospect of detecting insider threats based on leader-member exchange. This framework specifically corresponds to two propositions raised by Ho, Kaarst-Brown et al. [42]. Team members that are geographically co-located or dispersed are analogized as human sensors in social networks with the ability to collectively “react” to deception, even when the act of deception itself is not obvious to any one member. Close interactive relationships are the key to afford a network of human sensors an opportunity to formulate baseline knowledge of a deceptive insider. The research hypothesizes that groups unknowingly impacted by a deceptive leader are likely to use certain language-action cues when interacting with each other after a leader violates group trust.Item Modeling Expert Judgments of Insider Threat Using Ontology Structure: Effects of Individual Indicator Threat Value and Class Membership(2019-01-08) Greitzer, Frank; Purl, Justin; Becker, D.E. (Sunny); Sticha, Paul; Leong, Yung MeiWe describe research on a comprehensive ontology of sociotechnical and organizational factors for insider threat (SOFIT) and results of an expert knowledge elicitation study. The study examined how alternative insider threat assessment models may reflect associations among constructs beyond the relationships defined in the hierarchical class structure. Results clearly indicate that individual indicators contribute differentially to expert judgments of insider threat risk. Further, models based on ontology class structure more accurately predict expert judgments. There is some (although weak) empirical evidence that other associations among constructs—such as the roles that indicators play in an insider threat exploit—may also contribute to expert judgments of insider threat risk. These findings contribute to ongoing research aimed at development of more effective insider threat decision support tools.Item Introduction to the Minitrack on Inside the Insider Threats(2019-01-08) Clark, Jason; Bishop, Matt; Hoke, Candice