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Cyber-Investment and Cyber-Information Exchange Decision Modeling

机译:网络投资和网络信息交换决策模型

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摘要

Inefficiency of addressing cybersecurity problems can be settled by the corporations if they work in a collaborative manner, exchanging security information with each other. However, without any incentive and also due to the possibility of information exploitation, the firms may not be willing to share their breach/vulnerability information with the external agencies. Hence it is crucial to understand how the firms can be encouraged, so that they become self-enforced towards sharing their threat intelligence, which will not only increase their own payoff but also their peers' too, creating a win-win situation. In this research, we study the incentives and costs behind such crucial information sharing and security investments made by the firms. Specifically, a non-cooperative game between N-firms is formulated to analyze the participating firms' decisions about the information sharing and security investments. We analyze the probability of successful cyber attack using the famous dose-response immunity model. We also design an incentive model for CYBEX, which can incentivize/punish the firms based on their sharing/free-riding nature in the framework. Using negative definite Hessian condition, we find the conditions under which the social optimal values of the coupled constraint tuple (security investment and sharing quantity) can be found, which will maximize the firms' net payoff.
机译:如果公司以协作的方式工作,彼此交换安全信息,则可以解决解决网络安全问题的效率低下的问题。但是,在没有任何激励的情况下,并且由于有可能利用信息,这些公司可能不愿意与外部机构共享其违规/漏洞信息。因此,至关重要的是要理解如何鼓励公司,以便他们能够自我约束共享威胁情报,这不仅会增加自己的收益,而且也会增加他们的同行,创造双赢局面。在这项研究中,我们研究了企业进行此类至关重要的信息共享和安全投资背后的诱因和成本。具体而言,制定了N个公司之间的非合作博弈,以分析参与公司关于信息共享和安全投资的决策。我们使用著名的剂量反应免疫模型分析成功进行网络攻击的可能性。我们还为CYBEX设计了一种激励模型,该模型可以基于框架中公司的共享/搭便车性质来激励/惩罚公司。使用负的确定的Hessian条件,我们找到了可以找到耦合约束元组(证券投资和共享数量)的社会最优值的条件,这将使企业的净收益最大化。

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