Countering Insider Threat (CInT) Simulation
Abstract
As part of ARLIS' work to support the Department of Defense through the Countering Insider Threat program, the University of Maryland's ICONS Project was funded to develop and implement an online training exercise. The materials presented here are the content of that exercise which can function as a stand-alone, in-person tabletop, or can be conducted over the ICONSnet online platform for distributed use. The design of the exercise sees participants taking the roles of five key C-Suite executives (or their teams) at a fictional defense contractor, Kings Bay. All names and characters in the scenario are fictional. As the exercise unfolds, they are presented with a series of vignettes that highlight the challenges of dealing with different types of insider threats. A defense contractor was selected as the base for the scenario because of its connectivity to the various stages of work on programs that present differing profiles for insider threats: basic research, classified R and D, production, an interface/embedding directly with the government. Each of the vignettes that the participants receive focuses on a slightly different dilemma, ranging from potential espionage to information exposed due to human error, to the potential for workplace violence. For each, the differing C-Suite executives have their own individual goals and objectives based on their functions within the corporation - but also must have the wellbeing of the company, the employees, and the national security firmly in mind. Their objective is to propose a course of action to mitigate or resolve the issues raised in each vignette and present them to the facilitator. The learning objective is not to get a 'correct' answer to each dilemma - in some cases there might be multiple good solutions, or none. The objective, rather is to think more about how to tackle the hard problems in this space, and have an opportunity to learn through review and debriefing of the decisions they make.
Document Details
- Document Type
- Technical Report
- Publication Date
- Sep 30, 2021
- Accession Number
- AD1186392
Entities
People
- Adam Russell
- Devin Ellis
- Kelly Jones
- Ron Capps