Award Abstract # 2244283
NSF REU SITE: ASSET: Advanced Secured Sensor Enabling Technologies

NSF Org: CNS
Division Of Computer and Network Systems
Recipient: FLORIDA INTERNATIONAL UNIVERSITY
Initial Amendment Date: February 26, 2023
Latest Amendment Date: May 17, 2024
Award Number: 2244283
Award Instrument: Standard Grant
Program Manager: Ralph Wachter
rwachter@nsf.gov
 (703)292-8950
CNS
 Division Of Computer and Network Systems
CSE
 Directorate for Computer and Information Science and Engineering
Start Date: March 1, 2023
End Date: February 28, 2026 (Estimated)
Total Intended Award Amount: $405,000.00
Total Awarded Amount to Date: $425,000.00
Funds Obligated to Date: FY 2023 = $405,000.00
FY 2024 = $20,000.00
History of Investigator:
  • Niki Pissinou (Principal Investigator)
    pissinou@fiu.edu
Recipient Sponsored Research Office: Florida International University
11200 SW 8TH ST
MIAMI
FL  US  33199-2516
(305)348-2494
Sponsor Congressional District: 26
Primary Place of Performance: Florida International University
11200 SW 8TH ST
MIAMI
FL  US  33199-2516
Primary Place of Performance
Congressional District:
26
Unique Entity Identifier (UEI): Q3KCVK5S9CP1
Parent UEI: Q3KCVK5S9CP1
NSF Program(s): RSCH EXPER FOR UNDERGRAD SITES
Primary Program Source: 01002324DB NSF RESEARCH & RELATED ACTIVIT
01002425DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 9250, 9178, 9102
Program Element Code(s): 113900
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.070

ABSTRACT

This project is a renewal of a Research Experiences for Undergraduates (REU) Site at Florida International University that focuses on research related to advanced, secured sensor-enabled technologies. Undergraduates will work with faculty on research projects to explore new technologies and solutions utilizing sensor networks and protocols, software, and hardware solutions essential to the advancement and practical application of secure sensor technologies. This research theme includes a range of research projects, including adversarial machine learning attacks, efficient plausible deniability systems, resource-constrained multi-dimensional blockchains, vulnerability detection frameworks for securing ubiquitous systems, robust and secure wireless sensing systems for human activity recognition, and leveraging hybrid Li-Fi/Wireless sensor networks for internet of light. Undergraduates will participate in research that combines intellectual merit and technical opportunities. They will have a broad impact in m?health, vehicle platooning, cyberattacks, mobile crowd-sensing, and reduction of bias in data analytics. The program aims to nurture students into STEM research fields through a firsthand experience of an intense, interdisciplinary, collaborative research environment. All activities foster the development of collaborative communication among students and faculty to enhance and accelerate the students? research skills and learning in the field. If successful, the program will motivate students to continue relevant research careers, build human capacity in STEM research and knowledge, and increase workforce diversity.

This project combines the fields of sensing, computing, communications, and cybersecurity to create, develop, and implement new sensing concepts with innovative and significant knowledge. It pioneers core technologies, supportive algorithms, methods, architectures, and toolkits. The program provides a high-quality scientific and cross-cultural experience to motivated undergraduate students from underrepresented population groups nationwide. It aims to influence their choices about further education and future careers and increase their skills and confidence to pursue these choices. With specific recruiting efforts that target underrepresented groups such as women, minorities, and persons with disabilities, this REU program also aims to increase the diversity of the scientific workforce.

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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Alemany, Sheila and Pissinou, Niki and Yang, Brian "Increasing Adversarial Robustness Around Uncertain Boundary Regions with Amodal Segmentation" Proceedings , 2024 https://doi.org/10.1109/ICMLA61862.2024.00290 Citation Details
Alemany, Sheila and Worthington, Emma and Dominguez, Alberto and Grapel, Ilan and Pissinou, Niki "Unifying Robust Activation Functions for Reduced Adversarial Vulnerability with the Parametric Generalized Gamma Function" Proceedings , 2024 https://doi.org/10.1109/ICMLA61862.2024.00291 Citation Details

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