CPS: Synergy: Information Flow Analysis for Cyber-Physical System Security

该项目开发了一种既包括控制系统又包括计算系统的责任理论。网络物理系统(CPS)问责的统一理论可以建立在因果信息流分析的基础上，因果信息流分析是一套完善的计算机安全方法。信息流属性对系统的输入如何影响其输出进行建模。因果信息流概念为问责提供了有用的基础，因为它们支持可追溯性，即不仅可以检测违规行为，还可以分配责任，然后可以用来采取纠正措施。拟议项目的智力价值在于基于基于因果信息流分析的问责理论为CPS安全开发了一个统一的基础。更广泛的影响包括设计弹性和安全的CPS，这是维持一系列关键基础设施应用程序可靠运行的关键，以造福社会，如交通和智能电网系统。这个项目被组织成三个主要的推动力。关于攻击检测，该项目开发信息流分析，以支持对现实对手的被动和主动检测。首先，提出了以统一的方式恢复现有检测结果的信息流的一般框架。其次，信息流被用作分析工具，目的是在主动检测和隐形攻击特征方面产生新的结果。拟议的项目将使用这个框架来正式研究一组关于检测的一般问题。关于责任分配和识别，该项目寻求开发通过密码学和控制论的新方法组合来识别对攻击负责的节点的理论和方法。特别是，它将利用密码学中叛徒追踪的工具来高效地搜索包含恶意或故障实体的节点子集。它将使用控制理论中的方法来评估给定的节点子集是否行为不当或正常，并将调查控制和设计策略，以将信息流直接分配给不同的实体。最后一项任务是通过弹性系统设计和控制来制定纠正措施。这项任务旨在开发算法，以支持CP的弹性离线(资源分配)和在线(支持弹性在线控制的架构和算法)设计，并开发分析工具来评估组合下的CP的安全性。

This project develops a theory of accountability that encompasses both control and computing systems. A unified theory of accountability in Cyber-Physical Systems (CPS) can be built on a foundation of causal information flow analysis, a well-established set of methods for computer security. Information flow properties model how inputs of a system affect its outputs. Causal information flow notions provide a useful foundation for accountability since they support traceability, that is, not just detection of violations but also responsibility-assignment, which then can be used to adopt corrective measures. The intellectual merit of the proposed project lies in developing a unified foundation for CPS security based on theories of accountability, which build on causal information flow analysis. Broader impacts include the design of resilient and secure CPS, a key to sustaining reliable operation of a wide range of critical infrastructure applications for societal benefit, such as transportation and smart-grid systems. The project is organized into three major thrusts. With regards to attack detection the project develops information flow analyses to support passive and active detection against realistic adversaries. First, a general framework of information flows to recover existing results related to detection in a unified manner is proposed. Second, information flows are used as an analysis tool, with the goal of producing new results on active detection and stealthy attack characterization. The proposed project will employ this framework to formally study a set of general questions about detection. With respect to responsibility assignment and identification, the project seeks to develop theory and methodologies for identifying nodes responsible for an attack by a novel combination of methods from cryptography and control theory. In particular, it will leverage tools from traitor tracing in cryptography to efficiently search for subsets of nodes that contain malicious or faulty entities. It will employ methods from control theory to evaluate if given subsets of nodes are misbehaving or normal and it will investigate control and design policies to directly attribute information flows to distinct entities. The final task seeks to develop corrective measures via resilient system design and control. This task seeks to develop algorithms to support resilient offline (resource allocation) and online (architectures and algorithms that enable resilient online control) design of CPS and analysis tools to evaluate the security of CPS under composition.