Deception, which includes leading cyber-attackers astray with false information, has shown to be an effective method of thwarting cyber-attacks. There has been little investigation of the effect of probing action costs on adversarial decision-making, despite earlier studies on deception in cybersecurity focusing primarily on variables like network size and the percentage of honeypots utilized in games. Understanding human decision-making when prompted with choices of various costs is essential in many areas such as in cyber security. In this paper, we will use a deception game (DG) to examine different costs of probing on adversarial decisions. To achieve this we utilized an IBLT model and a delayed feedback mechanism to mimic knowledge of human actions. Our results were taken from an even split of deception and no deception to compare each influence. It was concluded that probing was slightly taken less as the cost of probing increased. The proportion of attacks stayed relatively the same as the cost of probing increased. Although a constant cost led to a slight decrease in attacks. Overall, our results concluded that the different probing costs do not have an impact on the proportion of attacks whereas it had a slightly noticeable impact on the proportion of probing.

翻译：欺骗，包括使用虚假信息引导网络攻击者误入歧途，已被证明是阻止网络攻击的有效方法。尽管先前关于网络安全中欺骗的研究主要集中在网络规模、游戏中使用的蜜罐比例等变量上，但针对探测行动成本对对抗决策影响的研究却很少。理解人类在面对不同成本选择时的决策过程，对于网络安全等多个领域至关重要。本文将通过一个欺骗博弈来研究不同探测成本对对抗决策的影响。为此，我们使用了基于实例的学习模型和延迟反馈机制来模拟人类行为的知识。我们的结果来自欺骗与无欺骗的均衡分割，以比较各自的影响。结论表明，随着探测成本的增加，探测行为略有减少。攻击比例在探测成本增加时保持相对稳定，尽管恒定成本导致攻击略有下降。总体而言，我们的结果认为，不同的探测成本对攻击比例没有影响，但对探测比例有轻微影响。