CPS: Medium: Collaborative Research: Security vs. Privacy in Cyber-Physical Systems
Lead PI:
Alvaro Cardenas
Co-PI:
Abstract
This research examines the scientific foundations for modeling security and privacy trade-offs in cyber-physical systems, focusing in particular on settings where privacy-protection technologies might be abused by malicious parties to hide their attacks. The goal is to provide both security and privacy guarantees for a variety of cyber-physical systems including intelligent transportation systems, smart energy, and autonomous vehicles. Privacy and security in cyber-physical systems have been studied independently before, but often they have not been addressed jointly.
Performance Period: 10/01/2018 - 05/31/2019
Institution: University of Texas at Dallas
Sponsor: National Science Foundation
Award Number: 1837627
CPS: Medium: Secure Computing and Cross-Layer Anomaly Detection in the Internet of Things
Lead PI:
Soummya Kar
Co-PI:
Abstract

This project tackles the following question: "Can a network of mutually-distrusting devices perform resilient inference and computation while detecting anomalous behaviors despite heterogeneity in the types of data they sense, the networking technologies they use and their computational capabilities?" The context is the increasingly pervasive Internet of Things (IoT) with low-power end users or sensors relying on edge devices to process their data, and possibly the cloud.

Performance Period: 01/01/2019 - 12/31/2023
Institution: Carnegie-Mellon University
Sponsor: National Science Foundation
Award Number: 1837607
CPS: Medium: Collaborative Research: Human-on-the-Loop Control for Smart Ultrasound Imaging
Lead PI:
Mostafa Fatemi
Co-PI:
Abstract
Due to low operating cost and patient safety, ultrasound is widely accepted as one of the best forms of medical imaging compared to similar technologies, such as Computer Tomography (CT) scans or Magnetic Resonance Imaging (MRI). Still, there can be large variability in image quality obtained by different experts imaging the same patient, which can affect successful diagnosis and patient treatment. This problem becomes even more pronounced across patients.
Performance Period: 10/01/2018 - 09/30/2021
Institution: Mayo Clinic Rochester
Sponsor: National Science Foundation
Award Number: 1837572
CPS: Medium: Collaborative Research: Security vs. Privacy in Cyber-Physical Systems
Jonathan Katz
Lead PI:
Jonathan Katz
Abstract
This research examines the scientific foundations for modeling security and privacy trade-offs in cyber-physical systems, focusing in particular on settings where privacy-protection technologies might be abused by malicious parties to hide their attacks. The goal is to provide both security and privacy guarantees for a variety of cyber-physical systems including intelligent transportation systems, smart energy, and autonomous vehicles. Privacy and security in cyber-physical systems have been studied independently before, but often they have not been addressed jointly.
Performance Period: 10/01/2018 - 09/30/2021
Institution: University of Maryland College Park
Sponsor: National Science Foundation
Award Number: 1837517
CPS:Small: Syntax-Guided Synthesis for Cyber-Physical Systems
Lead PI:
Hadas Kress-Gazit
Abstract

Nowadays, anyone can buy and put together sensors, actuators, and computation components, but typically only highly trained engineers are able to compose systems that can autonomously perform complex tasks. This project makes the design of cyber-physical systems (CPS) accessible to anyone by creating computational tools that enable people to choose a set of building blocks and define what a system should do. The tools then automatically create a simple and easy to understand description of how to assemble the components and provide the control needed to accomplish the task.

Performance Period: 10/01/2018 - 09/30/2024
Institution: Cornell University
Sponsor: National Science Foundation
Award Number: 1837506
CPS: Medium: Collaborative Research: Human-on-the-Loop Control for Smart Ultrasound Imaging
Lead PI:
Michael Zavlanos
Co-PI:
Abstract
Due to low operating cost and patient safety, ultrasound is widely accepted as one of the best forms of medical imaging compared to similar technologies, such as Computer Tomography (CT) scans or Magnetic Resonance Imaging (MRI). Still, there can be large variability in image quality obtained by different experts imaging the same patient, which can affect successful diagnosis and patient treatment. This problem becomes even more pronounced across patients.
Performance Period: 10/01/2018 - 09/30/2021
Institution: Duke University
Sponsor: National Science Foundation
Award Number: 1837499
CPS: TTP Option: Medium: Machine learning enabled "smart nets" to optimize sustainable fisheries technologies
Lead PI:
Jennifer Blain Christen
Co-PI:
Abstract
Fisheries employ 260 million people globally and fish are a primary animal protein source for roughly 40% of the world's population. Fishing effort has increased worldwide over the past few decades, leading to concerns over the incidental capture (termed "bycatch") of non-target species, especially endangered species such as sea turtles, sharks, and marine mammals. Globally, bycatch of sea turtles is especially problematic as recent estimates suggest that hundreds of thousands of turtles are killed annually in fishing gear, representing the greatest known threat to their continued survival.
Performance Period: 01/01/2019 - 12/31/2021
Institution: Arizona State University
Sponsor: National Science Foundation
Award Number: 1837473
CPS: TTP Option: Medium: Collaborative Research: Trusted CPS from Untrusted Components
Bruce McMillin
Lead PI:
Bruce McMillin
Co-PI:
Abstract
The nation's critical infrastructures are increasingly dependent on systems that use computers to control vital physical components, including water supplies, the electric grid, airline systems, and medical devices. These are all examples of Cyber-Physical Systems (CPS) that are vulnerable to attack through their computer systems, through their physical properties such as power flow, water flow, chemistry, etc., or through both. The potential consequences of such compromised systems include financial disaster, civil disorder, even the loss of life.
Performance Period: 10/01/2018 - 09/30/2021
Institution: Missouri University of Science and Technology
Sponsor: National Science Foundation
Award Number: 1837472
CPS: Medium: Edge-Cloud Support for Predictable, Global Situational-Awareness for Autonomous Vehicles
Lead PI:
Gabriel Parmer
Co-PI:
Abstract

The goal of this project is improved situation awareness for autonomous vehicles across many different networks. The approach is new theory and abstractions for systems where potentially moving physical systems join and leave the network at a high rate. Making these kinds of cyber-physical systems (CPS) efficient and safe requires leveraging the sensor information from other proximate vehicles over the network: this will enable vehicles to have much higher situational awareness--effectively seeing around corners.

Performance Period: 01/01/2019 - 12/31/2023
Institution: George Washington University
Sponsor: National Science Foundation
Award Number: 1837382
CPS: TTP Option: Medium: Collaborative Research: Trusted CPS from Untrusted Components
Lead PI:
Aditya Mathur
Abstract
The nation's critical infrastructures are increasingly dependent on systems that use computers to control vital physical components, including water supplies, the electric grid, airline systems, and medical devices. These are all examples of Cyber-Physical Systems (CPS) that are vulnerable to attack through their computer systems, through their physical properties such as power flow, water flow, chemistry, etc., or through both. The potential consequences of such compromised systems include financial disaster, civil disorder, even the loss of life.
Performance Period: 10/01/2018 - 09/30/2021
Institution: Purdue University
Sponsor: National Science Foundation
Award Number: 1837352
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