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Evaluating the agility of adaptive command and control networks from a cyber complex adaptive systems perspective

机译:从网络复杂的自适应系统角度评估自适应指挥与控制网络的敏捷性

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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.
机译:指挥和控制(C2)网络是现代军事系统的关键组成部分,可实现系统之间的信息共享和通信。这些系统在复杂的环境中运行,这些环境的特征是不确定的和不断发展的威胁,因此需要敏捷的C2网络。本文提出了一种网络复杂自适应系统方法,用于评估自适应C2网络的敏捷性。基于代理的建模用于模拟连接无人飞行器以执行协同监视任务的C2网络的性能。由于C2中信息共享的重要性,因此基于信息熵的认知度可用于定量评估C2性能。复杂的网络方法用于定义初始网络拓扑和威胁。通过随机重新布线进行的网络适应已显示出可在网络攻击后恢复丢失的C2功能,并且在某些情况下相对于初始拓扑可提高性能。逆平均路径长度和最大连接组成部分分数被证明是保持C2感知的重要因素,逆平均路径长度是感知的更好指标。

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