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

本项目发展了一种涵盖控制系统和计算系统的责任理论。网络物理系统（CPS）的责任统一理论可以建立在因果信息流分析的基础上，这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制提供了有用的基础，因为它们支持可追溯性，也就是说，不仅检测违规行为，而且还分配责任，然后可以使用责任分配来采取纠正措施。拟议项目的智力价值在于，基于建立在因果信息流分析基础上的问责理论，为CPS安全开发了统一的基础。更广泛的影响包括弹性和安全CPS的设计，这是维持广泛的关键基础设施应用可靠运行的关键，以实现社会效益，如交通和智能电网系统。该项目分为三个主要部分。在攻击检测方面，该项目开发了信息流分析，以支持针对现实对手的被动和主动检测。首先，提出了一个通用的信息流框架，以统一的方式恢复与检测相关的现有结果。其次，将信息流作为分析工具，目的是在主动检测和隐身攻击表征方面产生新的结果。拟议的项目将采用这个框架来正式研究一组关于检测的一般问题。在责任分配和识别方面，该项目寻求通过密码学和控制理论的新方法组合来开发识别负责攻击的节点的理论和方法。特别是，它将利用密码学中的叛逆者跟踪工具来有效地搜索包含恶意或错误实体的节点子集。它将采用控制理论的方法来评估给定的节点子集是行为不正常还是正常，它将研究控制和设计策略，以直接将信息流归因于不同的实体。最后一项任务是通过弹性系统设计和控制制定纠正措施。该任务旨在开发算法，以支持弹性离线（资源分配）和在线（实现弹性在线控制的架构和算法）CPS设计和分析工具，以评估组合下CPS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.