mlsanityData to 14 Oct 2026

Using Deep Learning to Detecting Deepfakes

arXiv 2207.13644 ↗First posted 27 Jul 2022cs.CV cs.AI cs.LGcited by 6

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Abstract (arXiv)

In the recent years, social media has grown to become a major source of information for many online users. This has given rise to the spread of misinformation through deepfakes. Deepfakes are videos or images that replace one persons face with another computer-generated face, often a more recognizable person in society. With the recent advances in technology, a person with little technological experience can generate these videos. This enables them to mimic a power figure in society, such as a president or celebrity, creating the potential danger of spreading misinformation and other nefarious uses of deepfakes. To combat this online threat, researchers have developed models that are designed to detect deepfakes. This study looks at various deepfake detection models that use deep learning algorithms to combat this looming threat. This survey focuses on providing a comprehensive overview of the current state of deepfake detection models and the unique approaches many researchers take to solving this problem. The benefits, limitations, and suggestions for future work will be thoroughly discussed throughout this paper.

Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Builds on 20 of its 41 references that are in the map. First posted on arXiv 27 Jul 2022.

Builds on

20 of 41 references.

References · 20

  1. 2014Very Deep Convolutional Networks for Large-Scale Image Recognitioncited by 15,364
  2. 2019FaceForensics++: Learning to Detect Manipulated Facial Imagescited by 1,101
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8 more
  1. 2021Applications of Recurrent Neural Network for Biometric Authentication & Anomaly Detectioncited by 15
  2. 2022Hold On and Swipe: A Touch-Movement Based Continuous Authentication Schema based on Machine Learningcited by 12
  3. 2021Machine Learning Algorithms In User Authentication Schemescited by 11
  4. 2020Dodging DeepFake Detection via Implicit Spatial-Domain Notch Filteringcited by 10
  5. 2021A Modern Analysis of Aging Machine Learning Based IoT Cybersecurity Methodscited by 10
  6. 2021Where Do Deep Fakes Look? Synthetic Face Detection via Gaze Trackingcited by 9
  7. 2022Machine and Deep Learning Applications to Mouse Dynamics for Continuous User Authenticationcited by 9
  8. 2021FakeBuster: A DeepFakes Detection Tool for Video Conferencing Scenarioscited by 6

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Cited by year

Citing papers per year: 2023: 5; 2024: 1.

6 papers.