Identity Verification in Smartphones as Social Intersectionality: Inclusive Design of Contactless Fingerprints to Mitigate Skin Tone and Gender Bias
Dr. Emanuela Marasco
KEY INTERESTS
Computer vision; Machine Learning; Deep learning; Cybersecurity; Biometrics
AFFILIATIONS/APPOINTMENTS
Assistant Professor, Information Sciences and Technology (IST) Department and Department of Computer Science, George Mason University
Center for Secure Information Systems (CSIS), George Mason University
ACADEMIC DEGREES
MSc, Computer Engineering, University of Naples Federico II
PhD, Computer and Automation Engineering, University of Naples Frederico II
IDENTITY VERIFICATION IN SMARTPHONES AS SOCIAL INTERSECTIONALITY: INCLUSIVE DESIGN OF CONTACTLESS FINGERPRINTS TO MITIGATE SKIN TONE AND GENDER BIAS
Technological discrimination, or the inability of AI-empowered security systems relying on optical sensors to properly extract salient features, is a challenge faced by marginalized people every day. This project aims to develop a contactless biometric mobile security application that can mitigate the vulnerabilities of deep AI and optical sensors and allow marginalized identities the same access to data security. The work will also identify the impact of physical vulnerabilities and use this data to retrain AI models to mitigate these vulnerabilities and protect users of all backgrounds.