自动化红队的演化模拟应用:初步研究

James Decraene, Mahinthan Chandramohan, M. Low, Chwee Seng Choo
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引用次数: 14

摘要

我们报告了应用于自动红队(ART)的可进化模拟的初步研究。ART是一种脆弱性评估工具,在该工具中,基于agent的简化军事场景模型被反复自动生成、执行和变化。利用自然启发的启发式技术来驱动模拟模型的探索,以展示所需的系统行为。迄今为止,抗逆转录病毒治疗的调查基本上是针对一组有限的固定参数的演变,这些参数决定了药物的行为。我们建议扩展ART以扩大可演化仿真模型参数的范围。使用这种“可进化模拟”方法,我们进行了智能体结构进化的实验。具体来说,研究了一个海上场景,其中交战船只的个别轨迹演变为打破蓝色。这些实验是使用一个模块化的进化框架来进行的。结果显示了反直觉的结果,并表明可进化模拟是一种很有前途的技术来增强ART。
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Evolvable simulations applied to Automated Red Teaming: A preliminary study
We report preliminary studies on evolvable simulations applied to Automated Red Teaming (ART). ART is a vulnerability assessment tool in which agent-based models of simplified military scenarios are repeatedly and automatically generated, executed and varied. Nature-inspired heuristic techniques are utilized to drive the exploration of simulation models to exhibit desired system behaviors. To date, ART investigations have essentially addressed the evolution of a limited fixed set of parameters determining the agents' behavior. We propose to extend ART to widen the range of evolvable simulation model parameters. Using this “evolvable simulation” approach, we conduct experiments in which the agents' structure is evolved. Specifically, a maritime scenario is examined where the individual trajectories of belligerent vessels are evolved to break Blue. These experiments are conducted using a modular evolutionary framework coined CASE. The results present counter-intuitive outcomes and suggest that evolvable simulation is a promising technique to enhance ART.
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