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A Novel Asset Authentication Scheme for Cyber Physical Systems

机译:网络物理系统的新型资产认证方案

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Cyber physical assets are being widely deployed. An asset could be a device or object in Cyber physical system (CPS). Many of them are subjected to compromise due to insecure implementations and configuration. Existing authentication techniques are not effective in detecting compromised assets given the massive scale of deployment. In this paper, we present a system for detecting compromised CPS assets effectively. In contrast to prior work, we propose an asset authentication framework that uses device-specific and network information with weight vectors, called slanted fingerprints, to validate assets. In particular, we perform asset fingerprinting with environmental effects to detect the cyber-physical emulation attacks on authentication. The framework tracks the effect of changes in the physical environment on fingerprints and uses unique CPS environmental effects features to detect both cyber-physical emulation and advanced stealthy attacks.
机译:网络物理资产正在广泛部署。资产可以是网络物理系统(CPS)中的设备或对象。由于不安全的实现和配置,它们中的许多受到损害。考虑到大规模的部署,现有的身份验证技术无法有效地检测出受侵害的资产。在本文中,我们提出了一种有效检测受侵害的CPS资产的系统。与先前的工作相反,我们提出了一种资产认证框架,该框架使用特定于设备的网络信息以及权重向量(称为倾斜指纹)来验证资产。尤其是,我们执行具有环境影响的资产指纹识别,以检测对身份验证的网络物理仿真攻击。该框架跟踪物理环境变化对指纹的影响,并使用独特的CPS环境影响功能来检测网络物理仿真和高级隐身攻击。

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