3 citations · 4 across the 5 of their papers we have counts for
6 papers
"What I See is What I Hear": Deepfake Detection Across Diverse Hearing Abilities
Magdalena Pasternak, Malvika Jadhav, Palavi V. Bhole +8
The proliferation of audiovisual deepfakes has lowered the cost of fraud, impersonation, and misinformation, but their success ultimately depends on human perception. Detection req…
Devilray: A Reconfigurable Adversarial Baseline for Revealing Blind Spots in Fake Base Station Detection
Taekkyung Oh, Duckwoo Kim, Hansung Bae +8
Fake Base Station (FBS) detection has been a critical focus of cellular security research for over two decades. However, significant financial and regulatory barriers to accessing…
Read This Paper to Get $50 Million:* An Analysis of Mobile Messaging Scams Using Reddit Data
Allison Lu, Bernardo B. P. Medeiros, Kevin R. B. Butler +1
Mobile messaging scams--fraudulent messages delivered over SMS and other mobile applications--have become a persistent and evolving security threat, yet the attributes underlying t…
Pitch Imperfect: Detecting Audio Deepfakes Through Acoustic Prosodic Analysis
Kevin Warren, Daniel Olszewski, Seth Layton +3
Audio deepfakes are increasingly in-differentiable from organic speech, often fooling both authentication systems and human listeners. While many techniques use low-level audio fea…
Analyzing the AI Nudification Application Ecosystem
Cassidy Gibson, Daniel Olszewski, Natalie Grace Brigham +5
Given a source image of a clothed person (an image subject), AI-based nudification applications can produce nude (undressed) images of that person. Moreover, not only do such appli…
Every Breath You Don't Take: Deepfake Speech Detection Using Breath
Seth Layton, Thiago De Andrade, Daniel Olszewski +3
Deepfake speech represents a real and growing threat to systems and society. Many detectors have been created to aid in defense against speech deepfakes. While these detectors impl…