Towards a Threat Model for Vehicular Fog Computing
Towards a Threat Model for Vehicular Fog Computing
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DOI：
10.1109/uemcon47517.2019.8993064
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发表时间：
2019-10
期刊：
影响因子：
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通讯作者：
Mohammad Aminul Hoque;Ragib Hasan
中科院分区：
文献类型：
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作者：
Mohammad Aminul Hoque;Ragib Hasan
由于网络规模庞大、节点的高移动性以及网络拓扑结构的不断变化，车用网络的安全性是一个巨大的挑战。这些挑战同样适用于车载雾，这是一种新的车载网络计算范式。在车载雾计算中，车辆作为雾节点。对于延迟敏感和位置感知服务来说，这是一个很有前途的模型，但也会产生一些独特的安全和隐私问题。然而，目前还缺乏一种系统的方法来使用综合威胁模型来设计车辆雾的安全解决方案。威胁建模是一个循序渐进的过程，用于分析、识别和确定系统的所有潜在威胁和漏洞的优先级，并使用已知的安全解决方案来解决它们。设计良好的威胁模型可以帮助您了解安全和隐私威胁、漏洞、需求和挑战，以及攻击者模型、攻击动机和攻击者能力。汽车雾计算中的威胁模型分析至关重要，因为只有头脑风暴和其他汽车网络范例的威胁模型不能提供潜在威胁和漏洞的完整场景。在本文中，我们探索了车载雾计算的威胁模型，并使用STRIDE和CIAA威胁建模流程识别了威胁和漏洞。我们认为这一举措将有助于改进车辆雾计算的安全和隐私系统设计。
Security is a huge challenge in vehicular networks due to the large size of the network, high mobility of nodes, and continuous change of network topology. These challenges are also applicable to the vehicular fog, which is a new computing paradigm in the context of vehicular networks. In vehicular fog computing, the vehicles serve as fog nodes. This is a promising model for latency-sensitive and location-aware services, which also incurs some unique security and privacy issues. However, there is a lack of a systematic approach to design security solutions of the vehicular fog using a comprehensive threat model. Threat modeling is a step-by-step process to analyze, identify, and prioritize all the potential threats and vulnerabilities of a system and solve them with known security solutions. A well-designed threat model can help to understand the security and privacy threats, vulnerabilities, requirements, and challenges along with the attacker model, the attack motives, and attacker capabilities. Threat model analysis in vehicular fog computing is critical because only brainstorming and threat models of other vehicular network paradigms will not provide a complete scenario of potential threats and vulnerabilities. In this paper, we have explored the threat model of vehicular fog computing and identified the threats and vulnerabilities using STRIDE and CIAA threat modeling processes. We posit that this initiative will help to improve the security and privacy system design of vehicular fog computing.