Computation is everywhere. Greeting cards have processors that play songs. Fireworks have processors for precisely timing their detonation. Computers are in engines, monitoring combustion and performance. They are in our homes, hospitals, offices, ovens, planes, trains, and automobiles. These computers, when networked, will form the Internet of Things (IoT). The resulting applications and services have the potential to be even more transformative than the World Wide Web. The security implications are enormous. Internet threats today steal credit cards. Internet threats tomorrow will disable home security systems, flood fields, and disrupt hospitals. The root problem is that these applications consist of software on tiny low-power devices and cloud servers, have difficult networking, and collect sensitive data that deserves strong cryptography, but usually written by developers who have expertise in none of these areas. The goal of the research is to make it possible for two developers to build a complete, secure, Internet of Things applications in three months. The research focuses on four important principles. The first is "distributed model view controller." A developer writes an application as a distributed pipeline of model-view-controller systems. A model specifies what data the application generates and stores, while a new abstraction called a transform specifies how data moves from one model to another. The second is "embedded-gateway-cloud." A common architecture dominates Internet of Things applications. Embedded devices communicate with a gateway over low-power wireless. The gateway processes data and communicates with cloud systems in the broader Internet. Focusing distributed model view controller on this dominant architecture constrains the problem sufficiently to make problems, such as system security, tractable. The third is "end-to-end security." Data emerges encrypted from embedded devices and can only be decrypted by end user applications. Servers can compute on encrypted data, and many parties can collaboratively compute results without learning the input. Analysis of the data processing pipeline allows the system and runtime to assert and verify security properties of the whole application. The final principle is "software-defined hardware." Because designing new embedded device hardware is time consuming, developers rely on general, overkill solutions and ignore the resulting security implications. The data processing pipeline can be compiled into a prototype hardware design and supporting software as well as test cases, diagnostics, and a debugging methodology for a developer to bring up the new device. These principles are grounded in Ravel, a software framework that the team collaborates on, jointly contributes to, and integrates into their courses and curricula on cyberphysical systems.

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.

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.

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.