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Smart, Connected and Secure Cities

Our faculty collaborate with cities across our region to evaluate and address risks to infrastructure, mobility, and communities, including major challenges like climate change. Together, we develop and deploy smart tools to support disaster preparation and response and recovery focusing particularly on technology-enabled and data-driven decision-making tools that improve resilience and coordination.

Secure and Resilient Cyber-Physical Systems

Cyber-physical systems (CPS) like smartphones, fitness trackers, and smart homes are part of our daily lives, but they’re also vulnerable to attack as high-profile cases have shown, leading to disruptions in supply chains, transportation, health care, military operations, and homeland security.  But never fear: Vanderbilt faculty member Xenofon Koutsoukos and a team of cutting-edge researchers affiliated with the Vanderbilt Institute for Software Integrated Systems are leading a $14 million, five-year, multi-university Science of Security Lablet sponsored by the National Security Agency to address this multi-faceted challenge. Working across multiple disciplines, Koutsoukos and his team are identifying patterns of complexity across disciplines and applications, developing principles for secure and resilient CPS in adversarial environments, designing integrated solutions to anticipate future conditions, and supporting operational decision-making and policy development to create greater cyber resilience.

In fact, faculty from the Vanderbilt Institute for Software Integrated Systems have already developed a wide range of tools to analyze and secure cyber-physical systems (Fig. 1).

Xenofon Koutsoukos - VU Cyber Security Tool Suites and Layers
Figure 1. High level overview of a wide variety of open-source tools suites and infrastructure layers already developed by Vanderbilt’s expert faculty for resilient cyber-physical systems.

Furthering efforts to advance cyber-physical system security, Koutsoukos and Vanderbilt colleagues Gabor Karsai and Janos Sztipanovits have collaborated with researchers from peer institutions on a $9M NSF-funded Foundations of Resilient Cyber-Physical Systems (FORCES) project to provide more resilient and secure CPS tools to support national health, energy, and transportation priorities (Fig. 2). As part of that collaboration, our Vanderbilt team successfully delivered an open tool integration framework, threat assessment and diagnostics, robust networked control, system-security co-design, and interdependent risk assessment.

Xenofon Koutsoukos NSF FORCES
Figure 2. The FORCES team is developing an evaluation framework for cyber resilience of different applications using using attacker-defender games modeling different environments and simulations using WebGME, Command and Control Wind Tunnel (C2WT) + Hardware-in-the-Loop (HIL) emulator.

Learn more about Vanderbilt faculty Xenofon Koutsoukos, Gabor Karsai, and Janos Sztipanovits, as well as the entire team at Vanderbilt’s Institute for Software Integrated Systems.

Enhanced Grid Flexibility and Renewables Integration

Microgrids can be great sources of renewable energy as well as reliable backup energy sources when main power grids are down, but they come with challenges like energy management and frequency control.  Vanderbilt faculty member Gabor Karsai is leading multiple projects focused on overcoming these challenges to unlock the full potential of microgrids, including a $2.5M DARPA-funded project with Abhishek Dubey to develop control software for highly localized microgrids that can address energy management functions ranging from alternating current power control mechanisms to management of inbound energy generated from photovoltaics and energy stored in batteries. Karsai’s research team at Vanderbilt is also working with colleagues at North Carolina State University to develop cyber-secure equipment and open-source microgrid control software to effectively manage renewable energy generation and power distribution. This project is based on the Resilient Information Architecture Platform for Smart Grids (RIAPS) developed by Vanderbilt and North Carolina State University, and is part of a $175M U.S. Department of Energy’s Advanced Research Projects Agency-Energy (ARPA-E) program to support novel approaches to clean energy challenges.

Karsai isn’t the only Vanderbilt faculty member working to make renewable energy sources more reliable:  Hiba Baroud and Sankaran Mahadevan are developing new algorithms that can help energy suppliers predict and plan operations in the face of fluctuating energy demand as well as fluctuations in energy output from renewable sources. Their approach minimizes costs and risk by using machine learning to forecast and manage supply and demand, taking into account random and uncertain factors like renewable energy generation, load fluctuation, extreme weather, and more. This work is part of a $3.25M project in collaboration with the Georgia Institute of Technology and the Midcontinent Independent Supply Operator (MISO), a power consortium that operates the grid in all or parts of 15 states. The project is one of 10 funded by ARPA-E’s Energy Resource Feedback, Optimization, and Risk Management (PERFORM) program.

Learn more about Vanderbilt faculty Gabor Karsai, Hiba Baroud and Sankaran Mahadevan.

Predicting and Preventing the Next Pandemic

As we’ve seen first-hand over the past few years, our connected world and changes in local climate can cause pandemics to spread and vector-borne diseases to break out. However, with the help of new technology, we can monitor and predict possible disease outbreaks early. That’s the goal of the “Computing the Biome” research team led by Vanderbilt faculty member Janos Sztipanovits. The project is built on Microsoft’s Premonition Platform and includes researchers from Microsoft Premonition led by Vanderbilt alumni Ethan Jackson (Senior Director at Microsoft Healthcare) and collaborators from Harris County Public Health, John Hopkins University, University of Pittsburgh Medical School, University of Washington, as well as Vanderbilt. The team has developed a real-time, artificial-intelligence-based, networked sensor and monitoring platform to predict disease outbreaks (Fig. 5). By integrating data across multiple sources from fully-automated mosquito viral load sampling and sewage samples to weather and geo data, the system can identify potential outbreaks so they can be contained quickly, much like a sprinkler system can detect and contain a fire before it spreads. Now, the system is ready to launch more broadly across the United States to get ahead of the next pandemic.

Watch this NSF video about the NSF Convergence Accelerator “Computing the Biome”, where the team is already deploying an AI platform for monitoring and predicting biothreats.
Figure 5. Picture of an intelligent trap to monitor mosquito-borne diseases and identify other pathogens (left) and screenshot of forecasted areas of mosquito activity in Houston, TX.

Learn more about Vanderbilt faculty Janos Sztipanovits.

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