DHS Summer Research Team Research Workshop

Tuesday, August 3, 2021

1:00 p.m. – 5:00 p.m. Central Time

Register here! 

The Critical Infrastructure Resilience Institute (CIRI) is hosting research teams as part of the DHS Summer Research Team (SRT) Program for Minority Serving Institutions. Four groups of faculty and students from three different universities are collaborating with CIRI researchers to conduct research projects throughout the summer, concluding with a virtual research workshop on August 3.

Please join us for part or all of the event!

Each faculty and student team will present for 30 minutes with 15 minutes of Q&A. We will break and reset between each group. The students will also record a poster presentation as part of our virtual CIRI SRT poster session – recording links and posters will be added to the CIRI website shortly before the workshop. More information on the virtual poster session to come soon.

1:00 p.m. – 1:45 p.m. Central Time

Blockchain: Harnessing Linked Distributed Ledger

Research Team: PI Dr. Dan Tamir, Students Maria Tomasso and Kian O’Ryan, Texas State University

CIRI advisors: CDR Blair Sweigart and Dr. Joe DiRenzo, U.S. Coast Guard R&D Center

 

The team has been researching how blockchain can be used by the U.S. Coast Guard to improve their operations. Through a comparative study, the group hopes to deliver a proof-of-concept that will analyze the U.S. Coast Guard’s operations systems to see if these systems could be better managed by blockchain and what would be the cost benefits of moving operations to such a system.

2:00 p.m. – 2:45 p.m. Central Time

Enhancing Cybersecurity KSAs (Knowledge, Skills, and Abilities) for Cyber Education and Workforce Development

Research Team: PI Dr. Dan J. Kim, Students Max Douglas and Jordan Bernot, University of North Texas

CIRI advisor: Casey O’Brien, Information Trust Institute, University of Illinois Urbana-Champaign

 

As cyber-attacks become increasingly common and complex, cybersecurity workers need to have the skills and knowledge to deal with an ever-changing landscape. The research team plans to compare cybersecurity workforce frameworks including the new NICE Workforce Framework and map the components, functions, tasks, and roles of cybersecurity workers in order to set the industry up for future success. They will identify relationships among cybersecurity job associative components using the NICE Framework to collect potentially new job components in priority technology areas and will use this knowledge to develop an assessment and training module for these jobs.

3:00 p.m. – 3:45 p.m. Central Time

Evaluating Ontologies for Cybersecurity Workforce Development Applications

Research Team: PI Dr. Dipak Pravin, Students Ana Robinson and Jarod Costello, University of North Texas

CIRI advisor: Jose Medina Cruz, CIRI, University of Illinois Urbana-Champaign

 

This team hopes to improve upon the CyberTalent Bridge (CTB) a recommender tool developed by CIRI to help cybersecurity managers in assign tasks to their workforce. Specific project goals include reviewing the NICE Framework in how it compares to the CTB platform, map the tasks required of CTB and test the Framework, research machine learning to define a framework for mapping ontologies between relevant standards with a view that such a framework will form the basis for recommendations engine for CTB in the future.

 

4:00 p.m. – 4:45 p.m. Central Time

Integration of Vehicle-Based Sensing and Vehicle Dynamic Model in Evaluating Resilience of Highway Infrastructure

Research Team: PI Dr. Chun-Hsing Ho, Students Manuel Lopez, Jr. and Jimmie Devany, Northern Arizona University

CIRI advisors: Dr. Imad Al-Qadi and Xiuyu Liu, Illinois Center for Transportation (ICT), University of Illinois Urbana-Champaign

 

This research addresses one of current issues related to pavement conditions in highway infrastructure. The work is to develop an integrated methodology using a theoretical solution and a vehicle-based sensing system that can be utilized to predict roadway roughness and evaluate the resilience of highway infrastructure systems. GIS mapping and a full car model are used to select vibration data for analysis. Based on computing results, there is a strong correlation between the field vibration data and international roughness index (IRI) values. In addition, the dynamic modeling simulation and measurement are in a good agreement. The project concludes the integration of pavement sensing and dynamic modeling can be a promising method to determine roadway conditions.