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CPS: Medium: Collaborative Research: Against Coordinated Cyber and Physical Attacks: Unified Theory and Technologies

CPS: Medium: Collaborative Research: Against Coordinated Cyber and Physical Attacks: Unified Theory and Technologies
CPS:媒介:协作研究:对抗协调的网络和物理攻击:统一理论和技术
批准号:
1739886
负责人:
Xiaofeng Wang
金额:
$30.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-09-01 至 2021-08-31

项目摘要

项目成果

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中文摘要
翻译
协同网络物理攻击(CCPA)多年来一直被吹捧为一种严重的威胁,其中“协同”意味着攻击者完全了解物理工厂和状态,有时甚至可以制造物理缺陷,以协助网络攻击,反之亦然。近年来,这些攻击已经从理论变成了现实,对车辆、电网和工业工厂的攻击,有可能在数字世界之外造成破坏甚至死亡。CCPA在网络物理系统(CPS)安全方面提出了独特的挑战。历史上,防御网络攻击和物理攻击的技术是在不同的假设和模型下分开发展的。例如,网络安全技术通常需要完整的物理动态概况和对系统状态的观察,而当存在物理缺陷时,这些可能无法获得。同样,现有的系统控制技术可以有效地补偿物理损坏,但前提是控制软件和传感器数据不会受到损害。针对CCPA缺乏统一的方法。有了这个观察,这个项目关注于统一模型的开发,这些模型具有一致的假设集,由集成技术支持,在此基础上CCPA可以得到更有效的保护。为了建立弹性CPS架构的理论基础和工程原理,该项目将研究统一的模型和平台,这些模型和平台代表了对弹性CPS与CCPA的科学理解。CPS的工程将通过开发和集成降低复杂性的软件架构及其设计原则来解决,这将导致具有更高水平系统弹性的可验证和可认证架构。CPS技术将通过设计新的攻击检测、隔离和恢复工具以及定时和控制技术来解决,以确保对CCPA做出适当的响应。拟议的内在跨学科研究将确保弹性CPS的可预测性能,通过利用以下学科进展:(1)鲁棒容错控制系统的设计和评估,在高度不可预测的环境中显著提高安全水平;(ii)复杂性降低架构的设计和实现,将验证时间从数小时显著减少到数秒;(iii)开发多速率采样数据控制和鲁棒的基于可达性的攻击检测技术,确保传感器数据的可靠性;(iv)发展网络物理协同适应,优化控制性能和计算任务调度,以保证系统安全和有效地从CCPA中恢复。本项目的目标应用是无人机。研究结果将在三个不同的测试平台上进行评估:无人机测试平台、通用运输模型(GTM)飞机和电力系统虚拟测试平台(VTB)。该项目的技术进步将为当今CPS面临的安全性和可靠性问题提供解决方案,并提供可靠的CPS,适用于复杂和潜在敌对的网络环境,而不会牺牲功能或可访问性。该项目的成果将在档案期刊出版物、会议场所和各种讲习班和讲座中进行交流,并将在不同的学术水平上进行整合。
英文摘要
Coordinated cyber-physical attacks (CCPA) have been touted as a serious threat for several years, where "coordinated" means that attackers have complete knowledge of the physical plant and status, and sometimes can even create physical defects, to assist cyber attacks, and vice versa. In recent years, these attacks have crept from theory to reality, with attacks on vehicles, electrical grids, and industrial plants, which have the potential to cause destruction and even death outside of the digital world. CCPA raise a unique challenge with respect to cyber-physical systems (CPS) safety. Historically, technologies to defend cyber attacks and physical attacks are developed separately under different assumptions and models. For instance, cyber security technologies often require the complete profile of the physical dynamics and the observation of the system state, which may not be available when physical defects exist. Similarly, existing system control techniques may efficiently compensate for the physical damage, but under the assumption that the control software and the sensor data are not compromised. There is a lack of unified approaches against CCPA. With this observation, this project focuses on the development of unified models with coherent set of assumptions, supported by integrated technologies, upon which CCPA can be defended much more effectively.To establish theoretical foundations and engineering principles for resilient CPS architectures, this project will investigate unified models and platforms that represent the scientific understanding of resilient CPS against CCPA. Engineering of CPS will be addressed through the development and integration of complexity-reduced software architectures, along with their design principles, which lead to verifiable and certifiable architectures with higher level of system resilience. Technology of CPS will be addressed through the design of new attack detection, isolation, and recovery tools as well as timing and control techniques to ensure appropriate responses to CCPA. The proposed inherently interdisciplinary research will ensure predictable performance for resilient CPS, by leveraging the disciplinary advances in (i) the design and evaluation of robust fault-tolerant control systems yielding significantly enhanced levels of safety in highly unpredictable environments; (ii) the design and implementation of complexity reduction architecture yielding a significant reduction in the verification time from hours to seconds; (iii) the development of multi-rate sampled-data control and robust reachability-based attack detection techniques ensuring that the sensor data is reliable; and (iv) the development of cyber-physical co-adaptation that optimizes control performance and computation task scheduling to guarantee system safety and efficient recovery from CCPA. The target application of this project is unmanned aerial vehicles (UAVs). The research results will be evaluated in three different testbeds: UAV testbed, generic transportation model (GTM) aircraft, and power system virtual testbed (VTB). The technological advancement from this project will provide solutions for the safety and reliability issues faced by today's CPS and deliver dependable CPS that are applicable without sacrificing functionality or accessibility in complex and potentially hostile networked environment. The results of this project will be communicated in archival journal publications, conference venues and various workshops and lectures, and will be integrated at different academic levels.
期刊论文(5)
专著(0)
科研奖励(0)
会议论文
DOI: 10.1109/cdc.2018.8619331
发表时间: 2018-12
期刊: 2018 IEEE Conference on Decision and Control (CDC)
影响因子: --
作者: [Ying Shen;Xiaofeng Wang;Zhengguang Wu]
通讯作者: Ying Shen;Xiaofeng Wang;Zhengguang Wu
Lebesgue-Approximation-Based Model Predictive Control for Nonlinear Sampled-Data Systems with Measurement Noises
具有测量噪声的非线性采样数据系统的基于勒贝格近似的模型预测控制
DOI: 10.23919/acc.2018.8431194
发表时间: 2018
期刊: American Control Conference
影响因子: --
作者: [Yang, Lixing, Wang, Xiaofeng]
通讯作者: Wang, Xiaofeng
Collaborative Research: SLES: Guaranteed Tubes for Safe Learning across Autonomy Architectures
NRI: INT: COLLAB: Synergetic Drone Delivery Network in Metropolis
Virus-host interactions in the assembly of positive-strand RNA virus replication complexes
NRI: Collaborative Research: ASPIRE: Automation Supporting Prolonged Independent Residence for the Elderly
海外基金