Award Abstract # 1900187
Collaborative Research: Excellence In Research: Computational Framework and Data Science for Identification

NSF Org: CNS
Division Of Computer and Network Systems
Recipient: NORTH CAROLINA AGRICULTURAL AND TECHNICAL STATE UNIVERSITY
Initial Amendment Date: June 6, 2019
Latest Amendment Date: July 11, 2025
Award Number: 1900187
Award Instrument: Standard Grant
Program Manager: Subrata Acharya
acharyas@nsf.gov
 (703)292-2451
CNS
 Division Of Computer and Network Systems
CSE
 Directorate for Computer and Information Science and Engineering
Start Date: October 1, 2019
End Date: September 30, 2026 (Estimated)
Total Intended Award Amount: $700,001.00
Total Awarded Amount to Date: $1,004,822.00
Funds Obligated to Date: FY 2019 = $700,001.00
FY 2021 = $140,000.00

FY 2022 = $164,821.00
History of Investigator:
  • Kaushik Roy (Principal Investigator)
    kroy@ncat.edu
  • Albert Esterline (Co-Principal Investigator)
  • Xiaohong Yuan (Co-Principal Investigator)
Recipient Sponsored Research Office: North Carolina Agricultural & Technical State University
1601 E MARKET ST
GREENSBORO
NC  US  27411
(336)334-7995
Sponsor Congressional District: 06
Primary Place of Performance: North Carolina A&T State University
1601 E. Market Street
Greensboro
NC  US  27411-0001
Primary Place of Performance
Congressional District:
06
Unique Entity Identifier (UEI): SKH5GMBR9GL3
Parent UEI:
NSF Program(s): HBCU-EiR - HBCU-Excellence in,
HBCU-EiR - HBCU-Excellence in
Primary Program Source: 01002122DB NSF RESEARCH & RELATED ACTIVIT
01002223DB NSF RESEARCH & RELATED ACTIVIT

01001920DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 102Z, 041Z
Program Element Code(s): 070y00, 070Y00
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.070, 47.083

ABSTRACT

This project will enhance the data science capabilities and capacities at two historically black colleges and universities: North Carolina A&T State University and Winston-Salem State University. These institutions will provide graduate programs to their students and enable the future workforce. More precisely, the project aims 1) to enhance research capabilities in identity and data science and technology; 2) to enhance the capacity of North Carolina A&T State University and Winston-Salem State University to participate in identity and data-science research; 3) to involve graduate and undergraduate students, especially members of underrepresented minorities and females, in data science and identity research; and 4) to strengthen the North Carolina A&T computer science doctoral and Master's programs and the Winston-Salem State Master's program as well as to strengthen the pipeline to computer science doctoral studies.

Identity is an emerging critical research field thanks in part to the digitization of life and the accompanying threats. Data science helps by opening new opportunities for identifying and verifying persons in both cyberspace and the physical world for such tasks as authentication and intrusion detection. The project involves three thrusts. Thrust I involves enhancing an existing computational framework for identification. This thrust also involves extending the investigators' enhancement of the single-sign-on WebID protocol to allow virtually any authentication technique to be incorporated into the protocol, providing a platform for experimenting with applications of authentication from the other thrusts. Thrust II proposes authentication using periocular biometrics and active authentication using behavioral biometrics, and Thrust III will mitigate presentation attacks.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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Almalki, Sultan "An Empirical Evaluation of Online Continuous Authentication and Anomaly Detection Using Mouse Clickstream Data Analysis" Applied sciences , 2021 https://doi.org/https://doi.org/10.3390/app11136083 Citation Details
Alshareef, Norah "A Study of Gender Bias in Face Presentation Attack and Its Mitigation" Future internet , 2021 https://doi.org/https://doi.org/10.3390/fi13090234. Citation Details
David Johnson, Tony Gwyn "Deepfake Detection Using CNN Trained on Eye Region" International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems IEA/AIE 2022: Advances and Trends in Artificial Intelligence. Theory and Practices in Artificial Intelligence , 2022 Citation Details
David Johnson, Tony Gwyn "Deepfake Detection Using CNN Trained on Eye Region" International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems IEA/AIE 2022: Advances and Trends in Artificial Intelligence. Theory and Practices in Artificial Intelligence , 2022 Citation Details
Gwyn, Tony "Face Recognition Using Popular Deep Net Architectures: A Brief Comparative Study" Future internet , 2021 https://doi.org/https://doi.org/10.3390/fi13070164 Citation Details
Jeffrey J. Hernandez V., Rodney Dejournett "Face Authentication from Masked Face Images Using Deep Learning on Periocular Biometrics" International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems IEA/AIE 2022: Advances and Trends in Artificial Intelligence. Theory and Practices in Artificial Intelligence , 2022 https://doi.org/10.1007/978-3-031-08530-7_38 Citation Details
Jenkins, John and Roy, Kaushik and Shelton, Joseph "Using deep learning techniques and genetic-based feature extraction for presentation attack mitigation" Array , v.7 , 2020 Citation Details
Mason, Janelle and Dave, Rushit and Chatterjee, Prosenjit and Graham-Allen, Ieschecia and Esterline, Albert and Roy, Kaushik "An Investigation of Biometric Authentication in the Healthcare Environment" Array , v.8 , 2020 https://doi.org/10.1016/j.array.2020.100042 Citation Details
Richardson, Takiva and Shelton, Joseph and Eady, Yasmin and Kyei, Kofi and Esterline, Albert "WebID + biometrics with permuted disposable features" ACM SE '22: Proceedings of the 2022 ACM Southeast Conference , 2022 https://doi.org/10.1145/3476883.3524050 Citation Details

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