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.

Cyber-physical systems (CPS) are deployed in safety-critical and mission-critical applications for which security is a primary design concern. At the same time, these systems must be designed to be more flexible to changing requirements and environment conditions. This project pursues foundational work on a new methodology for CPS design to enable a "plug-and-play" approach that also ensures the security and safety of the system from the design phase. Such a principled design approach can have an enormous positive impact on the emerging national "smart" infrastructure. Through collaborations with industry partners, the project aims to improve the design process in the CPS industry with a particular focus on automotive systems. Additionally, this project plans to integrate research into undergraduate and graduate coursework, especially capstone projects, and will have an impact on the textbooks and online course content developed by the researchers. This project develops a fundamentally new theory for quantitative contract-based design of CPS that balances security requirements with critical safety and performance concerns. This theory meets a pressing need faced by industrial cyber-physical systems, which are being transformed by a push towards "plug-and-play" design architectures. This push tends to upend the design process for CPS, bringing with it renewed concerns about security and privacy. The proposed approach has the following key components: (i) a precise interface specification for each "plug-in" component in a novel quantitative temporal logic; (ii) rapid, run-time verification methods for checking component conformance to specifications, and (iii) A new approach for mapping components onto existing architectures while satisfying performance and security specifications, and minimizing costs. The approach will be developed and evaluated in an industrial automotive context. The proposed rigorous logic-based formalism, backed by algorithmic advances in verification and synthesis, has the potential to create new fundamental science and help put the industrial trend towards plug-and-play architectures on a firm footing.

This proposal will establish a framework for developing distributed Cyber-Physical Systems operating in a Networked Control Systems (NCS) environment. Specific attention is focused on an application where the computational, and communication challenges are unique due to the sheer size of the physical system, and communications between system elements include potential for significant losses and delays. An example of this is the power grid which includes large-scale deployment of distributed and networked Phasor Measurement Units (PMUs) and wind energy resources. Although, much has been done to model and analyze the impact of data dropouts and delay in NCS at a theoretical level, their impact on the behavior of cyber physical systems has received little attention. As a result much of the past research done on the `smart grid' has oversimplified the `physical' portion of the model, thereby overlooking key computational challenges lying at the heart of the dimensionality of the model and the heterogeneity in the dynamics of the grid. A clear gap has remained in understanding the implications of uncertainties in NCS (e.g. bandwidth limitations, packet dropout, packet disorientation, latency, signal loss, etc.) cross-coupled with the uncertainties in a large power grid with wind farms (e.g. variability in wind power, fault and nonlinearity, change in topology etc.) on the reliable operation of the grid. To address these challenges, this project will, for the first time, develop a modeling framework for discovering hitherto unknown interactions through co-simulation of NCS, distributed computing, and a large power grid included distributed wind generation resources. Most importantly, it addresses challenges in distributed computation through frequency domain abstractions and proposes two novel techniques in grid stabilization during packet dropout. The broader impact lies in providing deeper understanding of the impact of delays and dropouts in the Smart Grid. This will enable a better utilization of energy transmission assets and improve integration of renewable energy sources. The project will facilitate participation of women in STEM disciplines, and will include outreach with local Native American tribal community colleges This project will develop fundamental understanding of impact of network delays and drops using an approach that is applicable to a variety of CPS. It will enable transformative Wide-Areas Measurement Systems research for the smart grid through modeling adequacy studies of a representative sub-transient model of the grid along with the representation of packet drop in the communication network by a Gilbert model. Most importantly, fundamental concepts of frequency domain abstraction including balanced truncation and optimal Hankel-norm approximation are proposed to significantly reduce the burden of distributed computing. Finally, a novel `reduced copy' approach and a `modified Kalman filtering' approach are proposed to address the problem of grid stabilization using wind farm controls when packet drop is encountered.