Secure Mechanism of Intelligent Urban Railway Cloud Platform Based on Zero-trust Security Architecture

Y. Qlu
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Abstract

Aiming to strengthen the stability of operation and maintenance of the urban rail transit network cloud platform at this stage, it is emerging to solve the security mechanism of the intelligent urban railway cloud platform. In this paper, we proposed a zero-trust network security solution for the rail transit system network construction. First, we built a zero-trust network construction for smart city rail transit at the architecture level, it can break the phenomenon of information security silo of rail transit line platform and minimize the system security risk based on a zero-trust network. Next, we focus on building a cloud security brain for urban rail transit networks and proposed the self-learning trust algorithm for a zero-trust network. Specifically, we illustrated the modified network model and constructed a dynamic updating user trust profile as the trustworthy access list. The parameters of the self-learning trust algorithm consist of the state, available chain road bandwidth, waiting for queue state of network traffic, linkage actions, and so on. We adopted a dynamic self-learning strategy for adjusting mitigation policy, the learning step predicted the state of the predetermined congestion and selected the rich links for execution. Finally, experiments show the efficiency of our secure mechanism of railway cloud platform based on zero-trust security architecture.
基于零信任安全架构的智慧城市轨道云平台安全机制
现阶段针对加强城市轨道交通网络云平台运行维护的稳定性,解决智慧城市轨道交通云平台的安全机制应运而生。本文针对轨道交通系统网络建设,提出了一种零信任网络安全解决方案。首先,我们在架构层面构建了智慧城市轨道交通的零信任网络建设,它可以打破轨道交通线路平台的信息安全孤岛现象,将基于零信任网络的系统安全风险降到最低。接下来,我们重点构建了城市轨道交通网络的云安全大脑,提出了零信任网络的自学习信任算法。具体来说,我们对改进后的网络模型进行了说明,并构建了一个动态更新的用户信任配置文件作为可信访问列表。自学习信任算法的参数包括网络流量的状态、可用链路带宽、等待队列状态、联动动作等。我们采用动态自学习策略调整缓解策略,学习步骤预测预定拥塞的状态并选择富链路执行。最后,通过实验验证了基于零信任安全架构的铁路云平台安全机制的有效性。
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