Cyber insider threat reduction
 

 

AFOSR-SBIR for "XL-CITR: Accelerated Learning for Cyber Insider Threat Reduction"

Edward Chow, Professor, received a research contract ($17.8k) from AFOSR SBIR Phase I subcontract through Tier 1 Performance Solutions.

Abstract

Military network environments will be subject to both internal and external threats for the foreseeable future. Internal threats to cyber networks from U.S. personnel receive little attention in comparison to external threats; yet, the consequences can be even more devastating. The lack of tools for understanding insider threat, analyzing risk mitigation alternatives, and communicating results exacerbates the problem. In addition to automatic defense systems, supervisors must be alert to behavioral markers of suspicious behavior or attitudes on the part of employees. Effective training of supervisors and the instructors who teach them would help the DoD take proactive measures to detect and prevent intrusions as they happen, and before they can do significant damage.

To address this challenge, the TIER1 Performance Solutions Team proposes to design and build XL-CITR (Accelerated Learning for Cyber Insider Threat Reduction), a training development system that will properly train supervisors to detect and thwart insider threats to cyber networks. UCCS will contribute by surveying the common insider attacks and related defenses, creating scenarios for the training of insider attack detection, prevention, and mitigation. A team of BI GDD students will create interactive and adaptive games integrated with these scenarios and the profile of trainee. The game module will also interact with Tier1 learning managing server in a secure communication channel to exchange the user profile, scores, and further training scenarios.