Trustworthy operation of next-generation complex power grid critical infrastructures requires mathematical and practical verification solutions to guarantee the correct infrastructural functionalities. This project develops the foundations of theoretical modeling, synthesis and real-world deployment of a formal and scalable controller code verifier for programmable logic controllers (PLCs) in cyber-physical settings. PLCs are widely used for control automation in industrial control systems. A PLC is typically connected to an engineering workstation where engineers develop the control logic to process the input values from sensors and issue control commands to actuators. The project focuses on protecting infrastructures against malicious control injection attacks on PLCs, such as Stuxnet, that inject malicious code on the device to drive the underlying physical platform to an unsafe state. The broader impact of this proposal is highly significant. It offers potential for real-time security for critical infrastructure systems covering sectors such as energy and manufacturing. The project's intellectual merit is in providing a mathematical and practical verification framework for cyber-physical systems through integration of offline formal methods, online monitoring solutions, and power systems analysis. Offline formal methods do not scale for large-scale platforms due to their exhaustive safety analysis of all possible system states, while online monitoring often reports findings too late for preventative action. This project takes a hybrid approach that dynamically predicts the possible next security incidents and reports to operators before an unsafe state is encountered, allowing time for response. The broader impact of this project is in providing practical mathematical analysis capabilities for general cyber-physical safety-critical infrastructure with potential direct impact on our national security. The research outcomes are integrated into education modules for graduate, undergraduate, and K-12 classrooms.

An appointed National Research Council committee will conduct the second phase of a study to consider future research goals and directions for foundational science in cybersecurity and how investments in foundational work support civilian and national security mission needs in the long term. It will consider relevant topics in social and behavioral sciences as well as more "traditional" cybersecurity topics. The committee will review current federal cybersecurity research strategies, plans, and programs as well as requirements for both civilian and national security applications. It will consider major challenge problems, explore proposed new directions, identify gaps in the current portfolio, consider the complementary roles of research in unclassified and classified settings, and consider how foundational work in an unclassified setting can be translated to meet national security objectives. In Phase 1, already completed with separate funding, the study committee conducted initial data gathering and analysis. In Phase 2, to be funded under this activity, the committee will undertake additional data-gathering, analysis and deliberations and produce a report providing a high-level roadmap for foundational cybersecurity research. Foundational cybersecurity research that yields yield new technologies and approaches is an important element of the nation's response to the cybersecurity challenge. The results of this study are expected to inform future activities by federal agencies that conduct cybersecurity research and federal coordinating bodies for IT and cybersecurity. It is also expected to inform cybersecurity researchers as well as industry -- which is both a developer and consumer of cybersecurity technologies and services -- about needs, opportunities, and future directions.

U.S. economic growth, energy security, and environmental stewardship depend on a sustainable energy policy that promotes conservation,efficiency, and electrification across all major sectors. Buildings are the largest sector and therefore an attractive target of these efforts: current Federal sustainability goals mandate that 50% of U.S.commercial buildings become net-zero energy by 2050. A range of options exists to achieve this goal, but financial concerns require a data-driven, empirically-validated approach. However, critical gaps exist in the energy and water measurement technology, and indoorclimate control science, needed to benchmark competing options, prioritize efficiency investments, and ensure occupant comfort. To address these challenges, this project proposes a new kind of "peel-and-stick" sensor that can be affixed to everyday objects to infer their contributions to whole-building resource consumption. To use the sensors, occupants or building managers simply tag end loads like a ceiling light, shower head, or range top. The sensors monitor the ambient conditions around a load and, using statistical methods,correlate those conditions with readings from existing electricity, gas, or water meters, providing individual estimates without intrusive metering. The sensors are built from integrated circuit technology laminated into smart labels, so they are small, inexpensive, and easy-to-deploy. The sensors are powered by the same ambient signals they sense, eliminating the need for periodic battery replacement or wall power. Collectively, these properties address cost and coverage challenges, and enable scalable deployment and widespread adoption. The intellectual merit of this proposal stems from the insight that the transfer and use of energy (and other resources) usually emits energy, often in a different domain, and that this emitted energy is often enough to intermittently power simple, energy-harvesting sensors whose duty cycle is proportional to the energy being transferred or used. Hence, the mere activation rate of the sensors signalsthe underlying energy use. The power-proportional relationship between usage activity and side channel harvesting, when coupled with state-of-the art, millimeter-scale, nano-power chips and whole-house or panel-level meters, enables small and inexpensive sensor tags that are pervasively distributed with unbounded lifetimes. But, networking and tasking them, and making sense of their data, requires a fundamental rethinking of low-power communications, control, and data fusion to abstract the intermittent, unreliable, and noisy sensor infrastructure into actionable information. This project's broader impact stems from an integrated program of education, research, and outreach that (i) creates a smart objects focused curriculum whose classroom projects are motivated by research needs, (ii) provides research experiences for undergraduates and underrepresented minorities, (iii) mentors students on all aspects of successful research from articulating hypotheses to peer-reviewing papers,(iv) disseminates teaching materials on embedded systems and research pedagogy, (v) produces students who bridge disciplines,operating at the intersection of measurement science, information technology, and sustainability policy, and (vi) translates scientific discovery and technical knowledge into beneficial commercial products through industry outreach and internships, and (vii) engages with the National Labs to ensure that the research addresses pressing problems.

Designing software that can properly and safely interact with the physical world is an important cyber-physical systems design challenge. The proposed work includes the development of a novel approach to designing planning and control algorithms for high-performance cyber physical systems. The new approach was inspired by statistical mechanics and stochastic geometry. It will (i) identify behavior such as phase transitions in cyber-physical systems and (ii) capitalize this behavior in order to design practical algorithms with provable correctness and performance guarantees. The algorithms developed through this research effort hold the potential for immediate industrial impact, particularly in the development of real-time robotic systems. These algorithms may strengthen the rapidly developing U.S. robotics industry. The proposed research activity will also vitalize the PI?s educational plans. Undergraduate and graduate courses that make substantial contributions to the embedded systems education at MIT will be developed. The classes will focus on provably-correct controller synthesis for cyber-physical systems, which is currently not thought at MIT. Undergraduate students will be involved in research activities.

This INSPIRE award is partially funded by the Cyber-Physical Systems Program in the Division of Computer and Network Systems in the Directorate for Computer and Information Science and Engineering, the Information and Intelligent Systems Program in the Division of Information and Intelligent Systems in the Directorate for Computer and Information Science and Engineering, the Computer Systems Research Program in the Division of Computer and Network Systems in the Directorate for Computer and Information Science and Engineering, and the Software and Hardware Foundations Program in the Division of Computing and Communications Foundations in the Directorate for Computer and Information Science and Engineering. Sound plays a vital role in the ocean ecosystem as many organisms rely on acoustics for navigation, communication, detecting predators, and finding food. Therefore, the 3D underwater soundscape, i.e., the combination of sounds present in the immersive underwater environment, is of extreme importance to understand and protect underwater ecosystems. This project is creating a transformative distributed ocean observing system for studying the underwater soundscape at revolutionary spatial (~100 meters) and temporal (~100 seconds) resolutions that is also able to simultaneously resolve small-scale ocean current flow. These breakthroughs are achieved using a distributed collective of small hydrophone-equipped subsurface floats, which utilize group management techniques and sensor fusion to understand the ocean soundscape in a Lagrangian manner. The ability to record soundscapes provides a novel sensing technology to understand the effects of sound on marine ecosystems and the role that sound plays for species development. Experiments off the coast of San Diego, CA, and a research campaign in the Cayman Islands provide concrete scientific studies that are tightly interwoven with the engineering research. Oceans are drivers of global climate, are home to some of the most important and diverse ecosystems, and represent a substantial contribution to the world's economy as a major source of food and employment. The technological and scientific advances in this project provide crucial tools to understand natural ocean resources, by studying soundscapes at spatio-temporal scales that were heretofore extremely burdensome and expensive to obtain.

Cyber-physical systems employed in transportation, security and manufacturing applications rely on a wide variety of sensors for prediction and control. In many of these systems, acquisition of information requires the deployment and activation of physical sensors, which can result in increased expense or delay. A fundamental aspect of these systems is that they must seek information intelligently in order to support their mission, and must determine the optimal tradeoffs as to the cost of physical measurements versus the improvement in information. A recent explosion in sensor and UAV technology has led to new capabilities for controlling the nature and mobility of sensing actions by changing excitation levels, position, orientation, sensitivity, and similar parameters. This has in turn created substantial challenges to develop cyber-physical systems that can effectively exploit the degrees of freedom in selecting where and how to sense the environment. These challenges include high-dimensionality of observations and the associated "curse of dimensionality", non-trivial relationships between the observations and the latent variables, poor understanding of models relating the nature of potential sensing actions and the corresponding value of the collected information, and lack of sufficient training data from which to learn these models. Intellectual Merit: The proposed research includes: (1) data-driven stochastic control theory for intelligent sensing in cyber-physical systems that incorporates costs/delays/risks and accounts for scenarios where models for sensing, decision-making, and prediction are unavailable or poorly understood. (2) Validation of control methods on a UAV sensor network in the real world domain of archaeological surveying. Broader Impacts: The proposed effort includes: (a) Outreach: planned efforts for encouraging participation of women and under-represented groups; (b) Societal impact: research will lead to novel concepts in environmental monitoring, traffic surveillance, and security applications. (c) Multi- disciplinary activities: Impacting existing knowledge in cyber-physical systems, sensor management, and statistical learning. Research findings will be disseminated through conferences presentations, departmental seminars, journal papers, workshops and special sessions at IEEE CDC and RSS; (d) Curriculum development through new graduate level courses and course projects.

This project's objective is to enable assertion-driven development and debugging of cyber-physical systems (CPS), in which required conditions are formalized as part of the design. In contrast with traditional uses of assertions in software engineering, CPS demand a tight coupling of the cyber with the physical, including in system validation. This project uses mathematical models of key physical attributes to guide creation of assertions, to identify inconsistent or infeasible assertions, and to localize potential causes for CPS failures. The goal is to produce methods and tools that use physical models to guide assertion-based verification of cyber-physical systems. An assertion language is being developed that is founded in mathematical logic while providing the familiarity of commonly used programming languages. This foundation enables new automated debugging techniques for CPS. By leveraging models that encode laws of physics and an automated decision procedure, the techniques being developed help identify causes of CPS failures by distinguishing inconsistent or infeasible physical states from valid ones. This model-based approach incorporates means to assess these physical states using both probabilistic and non-probabilistic measures. Two safety-critical applications guide the research and demonstrate the impact on the development of CPS: coordinated control of autonomous vehicles and monitoring and control of left-ventricular assist devices (LVADs). The focus on these safety-critical applications are motivational for recruiting and educating engineering students who have high expectations for how their lives should be enabled by computing advances. Further, this research advances methods needed to validate safe and effective CPS, promoting the public's confidence in their application to safety-critical systems.

This project explores balancing performance considerations and power consumption in cyber-physical systems, through algorithms that switch among different modes of operation (e.g., low-power/high-power, on/off, or mobile/static) in response to environmental conditions. The main theoretical contribution is a computational, hybrid optimal control framework that is connected to a number of relevant target applications where physical modeling, control design, and software architectures all constitute important components. The fundamental research in this program advances state-of-the-art along four different dimensions, namely (1) real-time, hybrid optimal control algorithms for power management, (2) power-management in mobile sensor networks, (3) distributed power-aware architectures for infrastructure management, and (4) power-management in embedded multi-core processors. The expected outcome, which is to enable low-power devices to be deployed in a more effective manner, has implications on a number of application domains, including distributed sensor and communication networks, and intelligent and efficient buildings. The team represents both a research university (Georgia Institute of Technology) and an undergraduate teaching university (York College of Pennsylvania) in order to ensure that the educational components are far-reaching and cut across traditional educational boundaries. The project involves novel, inductive-based learning modules, where graduate students team with undergraduate researchers.

This project, generalizing mean-field approaches from physics and chemistry for integrated design of scalable, network resource aware, distributed control strategies for multi-agent robotic systems, aims to develop macroscopic models that retain salient features of the underlying multi-agent robotic system and use these models in the design of distributed control strategies. For complex cyber physical systems, this promises to provide a novel design methodology that is potentially applicable to a large class of systems and, therefore, will result in foundational knowledge of use to the community at large. This high-risk, high-reward project integrates ideas from physics, chemistry, control theory, and robotics to develop new theoretical foundations for the design, validation, and improvement of coordination strategies for multi-agent robotic systems. The project's intellectual merit lies in the ensemble approach towards the design, validation, and improvement of cyber physical systems. Mean-field methods provide a system-level abstraction of the underlying distributed system while retaining the salient features of the various agent-level interactions. The generalization of these models to ensembles of interacting engineered systems provides new methods for designing distributed controllers that are sensitive to changing network resources and whose performance can be predicted and adjusted to achieve both the desired short-term and long-term performance specifications. Broader Impacts: The broader impacts of this project are twofold. First, the mean-field approach takes into account network resource usage and management, providing an integrated strategy for designing scalable decentralized control and coordination strategies. Second, different from biologically-inspired approaches, the mean-field approach enables the design of distributed coordination strategies whose performance can be systematically predicted and tuned to meet detailed performance specifications. This has the potential to unify various existing multi-agent coordination approaches. The research outcomes will be disseminated through publications in technical conferences and journals and incorporated into the PI's existing undergraduate and graduate curriculum and K-12 outreach efforts targeted at increasing female participation in STEM fields.