Visible to the public Biblio

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Sullivan, Daniel, Colbert, Edward, Cowley, Jennifer.  2018.  Mission Resilience for Future Army Tactical Networks. 2018 Resilience Week (RWS). :11—14.

Cyber-physical systems are an integral component of weapons, sensors and autonomous vehicles, as well as cyber assets directly supporting tactical forces. Mission resilience of tactical networks affects command and control, which is important for successful military operations. Traditional engineering methods for mission assurance will not scale during battlefield operations. Commanders need useful mission resilience metrics to help them evaluate the ability of cyber assets to recover from incidents to fulfill mission essential functions. We develop 6 cyber resilience metrics for tactical network architectures. We also illuminate how psychometric modeling is necessary for future research to identify resilience metrics that are both applicable to the dynamic mission state and meaningful to commanders and planners.

Pawlick, Jeffrey, Nguyen, Thi Thu Hang, Colbert, Edward, Zhu, Quanyan.  2019.  Optimal Timing in Dynamic and Robust Attacker Engagement During Advanced Persistent Threats. 2019 International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOPT). :1—8.
Advanced persistent threats (APTs) are stealthy attacks which make use of social engineering and deception to give adversaries insider access to networked systems. Against APTs, active defense technologies aim to create and exploit information asymmetry for defenders. In this paper, we study a scenario in which a powerful defender uses honeynets for active defense in order to observe an attacker who has penetrated the network. Rather than immediately eject the attacker, the defender may elect to gather information. We introduce an undiscounted, infinite-horizon Markov decision process on a continuous state space in order to model the defender's problem. We find a threshold of information that the defender should gather about the attacker before ejecting him. Then we study the robustness of this policy using a Stackelberg game. Finally, we simulate the policy for a conceptual network. Our results provide a quantitative foundation for studying optimal timing for attacker engagement in network defense.