Funded Research Grants

SANDY: Sparsification-Based Approach for Analyzing Network Dynamics

PI: Sajal K. Das
Award amount: $163,067
Award date: 9/1/17 to 8/31/20

The goal of this three-year project, Sparsification-based Approach for Analyzing Network Dynamics (SANDY), is to develop a suite of scalable parallel algorithms for updating dynamic networks for different problems that can be executed on a wide range of HPC platforms. Dynamic network analysis will enable researchers to study the evolution of complex systems in diverse disciplines, such as bioinformatics, social sciences, and epidemiology. The SANDY project is expected to initiate a new direction of research in developing parallel dynamic network algorithms that will benefit multiple analysis objectives (e.g., motif finding and network alignment) and application domains (e.g., epidemiology, health care).  [Read more] [Sept 24, 2018]



NeTS: JUNO2: Collaborative Research: STEAM: Secure and Trustworthy Framework for Integrated Energy and Mobility in Smart Connected Communities

PI: Sajal K. Das
Award amount: $91,090
Award date: 9/1/18 to 8/31/19

The rapid evolution of data-driven analytics, Internet of things (IoT) and cyber-physical systems (CPS) are fueling a growing set of Smart and Connected Communities (SCC) applications, including for smart transportation and smart energy. However, the deployment of such technological solutions without proper security mechanisms makes them susceptible to data integrity and privacy attacks, as observed in a large number of recent incidents. If not addressed properly, such attacks will not only cripple SCC operations but also influence the extent to which customers are willing to share data. This in turn will make trustworthiness in SCC applications very challenging. To address this, a synergistic team of researchers from the US and Japan, under the JUNO2 program, will collaborate on this project, called STEAM (Secure and Trustworthy framework for integrated Energy and Mobility) to develop a framework to ensure data privacy, data integrity, and trustworthiness in smart and connected communities.  [Read more] [Sept 24, 2018]


A sample Cyber-Physical system is a water treatment system in which each component is in its own security domain. Each portion of the process is monitored (each with a wise owl who is an oracle of knowledge) through a valuation V (its spyglass) from that domain to other domains that contain information from the physical owls, cyber owls, and knowledge in the form of invariants (the books) to ensure system operation. ” Figure courtesy of Sarah Martin.

CPS: TTP Option: Medium: Collaborative Research: Trusted CPS from Untrusted Components

PI: Bruce McMillin
Co-PI's: Rui Bo and Jonathan Kimball

Amount: $962,695
Time Period: 10/1/2018 - 09/30/2021

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. The proposed work significantly advances the science of protecting CPS by ensuring that the systems "do what they are supposed to do" despite an attacker trying to make them fail or do harm. In this convergent approach, the key is to tell the CPS how it is supposed to behave and build in defenses that make sure each component behaves and works well with others. The proposed work has a clear transition to industrial practice. It will also enhance education and opportunity by opening up securing society as a fascinating discipline for K-12 students to follow. 




GAANN: A Doctoral Program in Big Data, Machine Learning, and Analytics for Security and Safety

PI: Sanjay Madria
Co PI's: Jagannathan Sarangapani
Sajal Das
Award amount $199,000
Award date: 10/1/18 to 9/30/19

This GAANN research program is to contribute toward the national need to address Big Data, Machine Learning and Analytics for Cyber Security and Safety in terms of Research, Education and Training. Big data is transforming science and engineering with applications in cyber security, infrastructure monitoring, and ultimately society itself. Global technological leadership in this area is important for the United States and can be sustained by educating future leaders.  With new paradigms and technologies, big data and machine learning research continues with new innovative outcomes from both industry and academia. We recognize that one of the most effective means for designing, developing, and deploying big data systems and analytical solutions for cyber security is by making technical solutions and applications relatively quickly, while making these accessible to local and state entities as well as to the government in a timely manner.  [Read more]   [Dec 17, 2018]


Optimization of Electric Shuttle Fleet in an Automated Mobility District

PI: Sanjay Madria
Award amount $33,490
Award date: 01/22/19 to 08/01/19

ABSTRACT: The research is to design and  develop a high-performance distributed optimization system for electric shuttle routing in an automated mobility district. Also, the module will be transformed into a tool that can be used by city planners, and operations managers for a successful deployment of automated vehicle based on-demand mobility system. The outcome of this will be an optimal routing of electric shuttle to minimize mobility and energy, handling high number of on-demand requests through novel HPC/distributed optimization technique,  and the final goal is to enable solutions for automated electric fleet operations for on-demand mobility systems. Read more  [Feb 11, 2019]