Attack Graphs for Standalone Non-Public 5G Networks

Arpit Tripathi, A. Thakur, T. B. Reddy
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Abstract

Private Networks (also known as Non-Public Net-works) bring significant benefits to Industry 4.0. These networks are typically deployed on-premises of the enterprises, and their isolation from the public (consumer) networks improves the crucial aspects of security and reliability. Despite the isolation, insider attacks can be mounted on these networks. This paper analyses such attacks using attack patterns from Common Attack Pattern Enumerations and Classifications (CAPEC) database. The analysis uses attack graphs, to combine individual domains, in the context of human, device, and network vulner-abilities. The attack graphs help identify paths, the cumulative impact on the system, and possible defense techniques, including security controls to mitigate the impact. Using three sample attack graphs in the context of standalone private 5G networks, this paper analyses possible security mechanisms and captures the difference among legacy enterprise networks (including WiFi for limited mobility), public networks, and private networks.
独立非公共5G网络攻击图
专用网络(也称为非公用网络)为工业4.0带来了巨大的好处。这些网络通常部署在企业内部,它们与公共(消费者)网络的隔离提高了安全性和可靠性的关键方面。尽管这些网络是隔离的,但内部攻击仍然可以在这些网络上进行。本文利用CAPEC数据库中的攻击模式对这类攻击进行了分析。该分析使用攻击图,在人员、设备和网络漏洞的上下文中组合各个域。攻击图有助于识别路径、对系统的累积影响以及可能的防御技术,包括减轻影响的安全控制。本文使用独立私有5G网络背景下的三个示例攻击图,分析了可能的安全机制,并捕获了传统企业网络(包括用于有限移动的WiFi)、公共网络和私有网络之间的差异。
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