Computer Science Department MS Thesis Presentation Cole Oullette "Detection, Validation and Analysis of Deepfaking in Social Media"

Cole Oullette 

MS Student

WPI – Computer Science Department 

Tuesday, April 29, 2025

Time: 12:00 PM – 1:00 PM 

Location: Fuller Labs 141

Advisor: Professor Jun Dai

Reader: Professor Xiaoyan Sun

Abstract:

As AI continues to gain momentum and capture media attention, the prevalence of AI-generated voice, video, and image deepfakes on social media is rising dramatically. On some platforms, the AI attribution rate is estimated to be as high as 38.95%, and continuing to increase month over month. Despite significant efforts in the literature to detect and mitigate these synthetic media, a substantial amount of deepfaked content still circulates undetected.

This thesis investigates methods for identifying, classifying, validating, and analyzing deepfakes in the digital landscape. Furthermore, this project investigates the potentials of leveraging contextual insights through the analysis of user interactions with AI-generated content, and proposes a new technique to enhance the detection and mitigation of deepfakes across social media platforms. By outsourcing part of the overall detection computation to a distributed base of users, interaction-based detection could prove to be a successful tool in reducing the harmful effects of AI-generated deepfakes online.