Many practical systems such as smart grid, unmanned aerial vehicles (UAVs) and robotic networks can be categorized as cyber physical systems (CPS). A typical CPS consists of physical dynamics, sensors, communication network and controllers. The communication network is of key importance in CPS, since it mimics the nerve system in the human body. Hence, it is critical to study how the communication network in CPS should be analyzed and designed. Essentially, communications stem from the uncertainty of system under consideration; random perturbations increase the system uncertainty, which is reduced by the control actions in CPS. It is well known that entropy is a measure of system uncertainty. A unified framework of entropy is used for CPS, in which random perturbations create entropy while communications and controls provide negative entropy to compensate the entropy generation. The intellectual merits are the novel framework of entropy for bridging the communications and control in CPS and the new design criterion based on the entropy of system state for CPS. The project's broader significance and importance are the education of various levels of students, the dissemination of results to public, and the impact on everyday life such as the improved agility and robustness of power grids. This project applies the framework of entropy to study the interdependencies of communications and control, thus facilitating the analysis and design of communications in CPS. The following tasks are tackled in the project: (a) Entropy Flow Based Communication Capacity Analysis in which communications in CPS is analyzed by studying the entropy fields in the physical dynamics, thus providing an estimation on the scale (bits/second) of communication capacity budget; (b) Communication Network Topology Design in which the design of the network topology (either physical or logical) is tackled through both optimization-based or heuristic approaches; (c) Online Network Resource Scheduling which refines the network resource scheduling during the operation using both optimization-based and heuristic approaches, within the framework of entropy fields; (d) Hardware Emulation Testbed which delivers a co-simulation testbed based on real time digital power simulator (RTDS) and a communication simulator, in the context of smart grids. Based on the research, new courses are developed. K-12 outreach and various levels of undergraduate/graduate educations are incorporated into the research.

Security and privacy concerns in the increasingly interconnected world are receiving much attention from the research community, policymakers, and general public. However, much of the recent and on-going efforts concentrate on security of general-purpose computation and on privacy in communication and social interactions. The advent of cyber-physical systems (e.g., safety-critical IoT), which aim at tight integration between distributed computational intelligence, communication networks, physical world, and human actors, opens new horizons for intelligent systems with advanced capabilities. These systems may reduce number of accidents and increase throughput of transportation networks, improve patient safety, mitigate caregiver errors, enable personalized treatments, and allow older adults to age in their places. At the same time, cyber-physical systems introduce new challenges and concerns about safety, security, and privacy. The proposed project will lead to safer, more secure and privacy preserving CPS. As our lives depend more and more on these systems, specifically in automotive, medical, and Internet-of-Things domains, results obtained in this project will have a direct impact on the society at large. The study of emerging legal and ethical aspects of large-scale CPS deployments will inform future policy decision-making. The educational and outreach aspects of this project will help us build a workforce that is better prepared to address the security and privacy needs of the ever-more connected and technologically oriented society. Cyber-physical systems (CPS) involve tight integration of computational nodes, connected by one or more communication networks, the physical environment of these nodes, and human users of the system, who interact with both the computational part of the system and the physical environment. Attacks on a CPS system may affect all of its components: computational nodes and communication networks are subject to malicious intrusions, and physical environment may be maliciously altered. CPS-specific security challenges arise from two perspectives. On the one hand, conventional information security approaches can be used to prevent intrusions, but attackers can still affect the system via the physical environment. Resource constraints, inherent in many CPS domains, may prevent heavy-duty security approaches from being deployed. This proposal will develop a framework in which the mix of prevention, detection and recovery, and robust techniques work together to improve the security and privacy of CPS. Specific research products will include techniques providing: 1) accountability-based detection and bounded-time recovery from malicious attacks to CPS, complemented by novel preventive techniques based on lightweight cryptography; 2) security-aware control design based on attack resilient state estimator and sensor fusions; 3) privacy of data collected and used by CPS based on differential privacy; and, 4) evidence-based framework for CPS security and privacy assurance, taking into account the operating context of the system and human factors. Case studies will be performed in applications with autonomous features of vehicles, internal and external vehicle networks, medical device interoperability, and smart connected medical home.

This research addresses the science of Cyber-Physical Systems. In a multi-agent system, each agent is faced with the task of making decisions taking account of the objectives and actions of other agents, as well as the dynamics of the environment. In such a distributed system each agent receives measurements of its environment, and must infer both the state of the world as well as that of the other agents. The intellectual merits of this research are that it develops new efficient techniques for this information processing, which achieve run-time performance using algorithms that have low computational requirements. The project's broader significance and importance are that it will provide new mathematical and computational tools for use in many engineering applications, including the power grid, transportation networks, and other multi-agent systems, and will be transitioned to practice through professional activities such as workshops, development of educational material for graduates, undergraduates and teenagers, and outreach to industry. The underlying mathematical and computation tools for this research are based on new methods for statistical filtering in a dynamic setting. One of the most important techniques for the design of software control systems constructs state estimates which are sufficient statistics for the associated decision problem. However, conventional approaches to sufficient statistics and state estimation do not apply to the multi-agent setting. Recent results have given new sufficient statistics for this setting, and the research develops the theory and algorithms to allow these statistics to be used for multi-agent control of cyber-physical systems.

During the last decade, we have witnessed a rapid penetration of autonomous systems technology into aerial, road, underwater, and sea vehicles. The autonomy assumed by these vehicles holds the potential to increase performance significantly, for instance, by reducing delays and increasing capacity, while enhancing safety, in a number of transportation systems. However, to exploit the full potential of these autonomy-enabled transportation systems, we must rethink transportation networks and control algorithms that coordinate autonomous vehicles operating on such networks. This project focuses on the design and operation of autonomy-enabled transportation networks that provide provable guarantees on achieving high performance and maintaining safety at all times. The foundational problems arising in this domain involve taking into account the physics governing the vehicles in order to coordinate them using cyber means. This research effort aims to advance the science of cyber-physical systems by following a unique and radical approach, drawing inspiration and techniques from non-equilibrium statistical mechanics and self-organizing systems, and blending this inspiration with the foundational tools of queueing theory, control theory, and optimization. This approach may allow orders of magnitude improvement in the servicing capabilities of various transportation networks for moving goods or people. The applications include the automation of warehouses, factory floors, sea ports, aircraft carrier decks, transportation networks involving driverless cars, drone-enabled delivery networks, air traffic management, and military logistics networks. The project also aims to start a new wave of classes and tutorials that will create trained engineers and a research community in the area of safe and efficient transportation networks enabled by autonomous cyber-physical systems.

Smart grid includes two interdependent infrastructures: power transmission and distribution network, and the supporting telecommunications network. Complex interactions among these infrastructures lead to new pathways for attack and failure propagation that are currently not well understood. This innovative project takes a holistic multilevel approach to understand and characterize the interdependencies between these two infrastructures, and devise mechanisms to enhance their robustness. Specifically, the project has four goals. The first goal is to understand the standardized smart grid communications protocols in depth and examine mechanisms to harden them. This is essential since the current protocols are notoriously easy to attack. The second goal is to ensure robustness in state estimation techniques since they form the basis for much of the analysis of smart grid. In particular, the project shall exploit a steganography-based approach to detect bad data and compromised devices. The third goal is to explore trust-based attack detection strategies that combine the secure state estimation with power flow models and software attestation to detect and isolate compromised components. The final goal is to study reconfiguration strategies that combine light-weight prediction models, stochastic decision processes, intentional islanding, and game theory techniques to mitigate the spreading of failures and the loss of load. A unique aspect of smart grid security that will be studied in this project is the critical importance of timeliness, and thus a tradeoff between effectiveness of the mechanisms and the overhead introduced. The project is expected to provide practical techniques for making the smart grid more robust against failures and attacks, and enable it to recover from large scale failures with less loss of capacity. The project will also train students in the multidisciplinary areas of power systems operation and design, networking protocols, and cyber-physical security.

Epilepsy is one of the most common neurological disorders, affecting between 0.4% and 1% of the world's population. While seizures can be controlled in approximately two thirds of newly diagnosed patients through the use of one or more antiepileptic drugs (AEDs), the remainder experience seizures even on multiple medications. The primary impacts of the chronic condition of epilepsy on a patient are a lower quality of life, loss of productivity, comorbidities, and increased risk of death. Epilepsy is an intermittent brain disorder, and in localization-related epilepsy, which is the most common form of epilepsy, one or a few discrete brain areas (the seizure focus or seizure foci) are believed to be responsible for seizure initiation. More recent approaches with implantable electrical stimulation seizure control devices hold value as a therapeutic option for the control of seizures. These devices, directly or indirectly, target the seizure focus and seek to control its expression. In this project we will build a multichannel brain implantable device based on emerging cyber physical system (CPS) principles. This brain implantable CPS device will incorporate key design features to make the device dependable, scalable, composable, certifiable, and interoperable. The device will operate over the life of an animal, or a patient, and continuously record brain activity and stimulate the brain when seizure related activity is detected to abort an impending seizure. Episodic brain disorders such as epilepsy have a considerable impact on a patient's productivity and quality of life and may be life-threatening when seizures cannot be controlled with medications. The goal of this project is to create a second generation brain-implantable sensing and stimulating device (BISSD) based on emerging CPS principles and practice. The development of a BISSD as a exemplifies several defining aspects that inform and illustrate core CPS principles. First, to meet the important challenge of regulatory approval a composable, scalable and certifiable framework that supports testing in multiple species is proposed. Second, a BISSD must be wholly integrated with the patient and fully cognizant at every instant of brain state, including dynamic changes in both the normal and abnormal expression of brain physiology and therapeutic intervention. Thus, this project seeks a tight conjunction of the cyber solution that must monitor itself and monitor and stimulate the brain using implanted, adaptable, distributed, and networked electrodes, and the physical system which in this case is the intermittently failing human brain. Third, a BISSD must function for an extensive period of time, up to the life of the patient, because each surgery to place and retrieve a BISSD carries an attendant risk. This requirement necessitates a dependable solution, which this project seeks to reliably achieve through both an understanding of the brain's foreign body response and a unique hierarchical fault-tolerant design. Fourth, an advanced salient approaches to acquire, compress, and analyze sensor signals to achieve real-time monitoring and control of seizures is employed. This project should yield a powerful, scalable CPS framework for robust fault-tolerant implantable medical devices with real-time processing that can grow with advances in sensors, sensing modalities, time-series analysis, real-time computation, control, materials, power and knowledge of underlying biology. The USA has a competitive advantage in the control of seizures in medically refractory epilepsy. In the modern era, epilepsy surgery evolved in the USA in the 1970s and spread from here to other parts of the world. Similarly, the USA enjoys a competitive advantage in BISSDs, and success in this effort will enable the USA to build on and maintain this advantage. In addition to epilepsy, advances made here can be expected to benefit the treatment of other neurological and psychiatric brain disorders.

The objective of this project is to develop optimization and control techniques and integrate them with real-time simulation models to achieve load balancing in complex networks. The application case is the regional freight system. Freight moves on rail and road networks which are also shared by passengers. These networks today work independently, even though they are highly interdependent, and the result is inefficiencies in the form of congestion, pollution, and excess fuel consumption. These inefficiencies are observed for example by the peaks of demand across time and space. Inefficiencies exist in part due to lack of information and appropriate tools, and in part due to lack of policies and institutional structures that would promote more integrated operations. The problem is made even more complex due to the large quantities of real time data that will be available to inform the decision-making. This research develops the theoretical foundations of a new approach referred to as COSMO to balance loads across complex dynamical networks with temporal and spacial characteristics. In contrast to current practices where simple mathematical models are used to predict the states of the network the method employs computational simulation models that are far more accurate in estimating the states of the network by taking into account dynamics and complex interactions. The project develops the optimization and load balancing control segments of the cyber physical system and integrate them with real time network simulation models using freight transportation as the driving application area. The research also examines how identified barriers and policy issues/incentives can be incorporated as mathematical constraints and/or control variables in the optimized dynamic freight load balancing system. Data supporting the analysis may include freight characterization, traffic, weather, and other large data volumes. The project will utilize real time data from the port of Los Angeles /Long Beach area to validate the approach. The port of Los Angeles/Long Beach is the port of entry for much of the freight that enters the West Coast, and provides rich sets of data that will stimulate the model especially in regional transportation involving interaction between road/rail/port networks. This fundamental technology in this important transportation domain with direct applications to other large scale freight centers, can be applied to other application domains including networking and smart grid. Besides the broader impact derived from more efficient allocation of transportation resources, the project also provide educational outreach and produce course modules.

The wide-area measurement systems technology using Phasor Measurement Units (PMUs) has been regarded as the key to guaranteeing stability, reliability, state estimation, and control of next-generation power systems. However, with the exponentially increasing number of PMUs, and the resulting explosion in data volume, the design and deployment of an efficient wide-area communication and computing infrastructure is evolving as one of the greatest challenges to the power system and IT communities. The goal of this NSF CPS project is to address this challenge, and construct a massively deployable cyber-physical architecture for wide-area control that is fast, resilient and cost-optimal (FRESCO). The FRESCO grid will consist of a suite of optimal control algorithms for damping oscillations in power flows and voltages, implemented on top of a cost-effective and cyber-secure distributed computing infrastructure connected by high-speed wide-area networks that are dynamically programmable and reconfigurable. The value of constructing FRESCO is twofold (1) If a US-wide communication network capable of transporting gigabit volumes of PMU data for wide-area control indeed needs to be implemented over the next five years then power system operators must have a clear sense of how various forms of delays, packet losses, and security threats affect the stability of these control loops. (2) Moreover, such wide-area communication must be made economically feasible and sustainable via joint decision-making processes between participating utility companies, and testing how controls can play a potential role in facilitating such economics. Currently, there is very limited insight into how the PMU data transport protocols may lead to a variety of such delay patterns, or dictate the economic investments. FRESCO will answer all of these questions, starting from small prototypical grid models to those with tens of thousands of buses. Our eventual goal will be to make FRESCO fully open-source for Transition to Practice (TTP). We will work with two local software companies in Raleigh, namely Green Energy Corporation and Real-Time Innovations, Inc. to develop a scalable, secure middleware using Data-Distribution Service (DDS) technology. Thus, within the scope of the project, we also expect to enrich the state-of-the-art cloud computing and networking technologies with new control and management functions. From a technical perspective, FRESCO will answer three main research questions. First, can wide-area controllers be co-designed in sync with communication delays to make the closed-loop system resilient and delay-aware, rather than just delay-tolerant This is particularly important, as PMU data, in most practical scenarios, will have to be transported over a shared resource, sharing bandwidth with other ongoing applications, giving rise to not only transport delays, but also significant delays due to queuing and routing. Advanced ideas of arbitrated network control designs will be used to address this problem. The second question we address is for cost. Given that there are several participants in this wide-area control, how much is each participant willing to pay in sharing the network cost with others for the sake of supporting a system-wide control objective compared to its current practice of opting for selfish feedback control only Ideas from cooperative game theory will be used to investigate this problem. The final question addresses security how can one develop a scientific methodology to assess risks, and mitigate security attacks in wide-area control? Statistical and structural analysis of attack defense modes using Bayesian and Markov models, game theory, and discrete-event simulation will be used to address this issue. Experimental demos will be carried out using the DETER-WAMS network, showcasing the importance of cyber-innovation for the sustainability of energy infrastructures. Research results will be broadcast through journal publications, and jointly organized graduate courses between NCSU, MIT and USC.

Inherent vulnerabilities of information and communication technology systems to cyber-attacks (e.g., malware) impose significant security risks to Cyber-Physical Systems (CPS). This is evidenced by a number of recent accidents. Noticeably, current distributed control of CPS is not really attack-resilient (ensuring task completion despite attacks). Although provable resilience would significantly lift the trustworthiness of CPS, existing defenses are rather ad-hoc and mainly focus on attack detection. In addition, while network attacks have been extensively studied, resilient-to-malware distributed control has been rarely investigated. This project aims to bridge the gap. It aims to investigate provably correct distributed attack-resilient control of CPS. The project will focus on a representative class of CPS, namely unmanned-vehicle-operator networks, and its four main research thrusts are: (1) The development of a distributed attack-resilient control framework to ensure task completion of multiple vehicles despite network attacks and malware attacks, (2) The synthesis of novel distributed attack-resilient control algorithms to deal with network attacks, (3) The design of estimation algorithms to detect malware attacks on vehicles, and computationally efficient algorithms which allow clean vehicles to avoid the collision with the vehicles compromised by malware, and (4) The validation of the cost-effectiveness of the proposed distributed attack-resilient control framework via a principled systematic evaluation plan. The research findings profoundly impact CPS security of a variety of engineering disciplines beyond unmanned-vehicle-operator networks, including smart grid, smart buildings and intelligent transportation systems. The proposed research is interdisciplinary and involves interactions among security, control, distributed algorithms and robotics. This will lead to educational and training opportunities that cross traditional disciplinary boundaries for high-school, undergraduate and graduate students in STEM.