A Simulation-based Intelligent Tutoring System for Enhancing Decision Effectiveness in Computer Network Defensive Operations

Arguably the most crucial aspect of maintaining Computer Network Defense (CND) readiness is having adequate supply of highly trained personnel to serve on the frontlines. Training today is mostly limited to classrooms, books, and expensive seminars, all of which fail to provide the practical experience necessary to make effective decisions under pressure. We propose a new approach to training CND that marries an innovative and affordable approach to producing high-fidelity simulations of complex computer networks with an intelligent tutoring capability that enables effective automated performance measurement and feedback to optimize the training experience. The proposed distance-learning solution will provide hands-on scenario-based exercises augmented by automated tutoring to provide customized coaching, feedback, and after-action review. Our approach to simulation overcome barriers to simulator development through the exploitation of COTS network traffic simulators with commodity hardware running genuine operating systems and software applications. Through automated assessment, in-depth explanations of expert solutions, what-if analyses, and interactive dialogs, the tutor will address higher-level cognitive skills like pattern recognition, hypothesis formation and testing, and decision-making. The system will include an authoring tool for the development of custom scenarios by SMEs. Phase I prototype development will provide a solid foundation for complete implementation in Phase II.