Abstract

Command and control (C2) networks are critical components of modern military systems, enabling information sharing and communications between systems. These systems operate in complex environments characterized by uncertain and evolving threats, creating a need for agile C2 networks. This paper presents a Cyber Complex Adaptive Systems approach for assessing the agility of adaptive C2 networks. Agent-based modeling is used to simulate the performance of a C2 network connecting unmanned aerial vehicles for a collaborative surveillance mission. Due to the importance of information sharing in C2, information entropy-based awareness is used to quantitatively evaluate C2 performance. Complex network methods are used to define initial network topologies and threats. Network adaptation through random rewiring is shown to recover lost C2 capabilities following network attacks, and in some cases improve performance relative to initial topologies. Inverse average path length and largest connected component fraction are shown to be important factors for maintaining C2 awareness, with inverse average path length being the better indicator of awareness.

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