Machine Learning for Deepfake Detection

Abstract

We learned why we need detectors, but why do we need machine learning? Potential Dangers: >700k hours of video uploaded to YouTube daily; Deepfake apps can be run with push of a button; Deepfakes are generated with ML, logical then to think that we can detect them with ML; Castle defense. We need scalable detectors!

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Document Details

Document Type
Technical Report
Publication Date
Sep 23, 2022
Accession Number
AD1180868

Entities

People

  • Shannon K. Gallagher

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Change Detection
  • Data Sets
  • Deepfakes
  • Department Of Defense
  • Detection
  • Detectors
  • Discriminators
  • Engineering
  • Generators
  • Governments
  • Guarantees
  • Images
  • Learning
  • Machine Learning
  • Materials
  • Models
  • Patents
  • Software Development
  • Trademarks
  • Universities

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Cybersecurity.
  • Sensor Fusion and Tracking Systems.

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks