Deepfake Detection using Biological Features: A Survey
- URL: http://arxiv.org/abs/2301.05819v1
- Date: Sat, 14 Jan 2023 05:07:46 GMT
- Title: Deepfake Detection using Biological Features: A Survey
- Authors: Kundan Patil, Shrushti Kale, Jaivanti Dhokey, Abhishek Gulhane
- Abstract summary: This study describes the history of deepfake, its development and detection, and the challenges based on physiological measurements.
Deepfakes have been used to blackmail individuals, plan terrorist attacks, disseminate false information, defame individuals, and foment political turmoil.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Deepfake is a deep learning-based technique that makes it easy to change or
modify images and videos. In investigations and court, visual evidence is
commonly employed, but these pieces of evidence may now be suspect due to
technological advancements in deepfake. Deepfakes have been used to blackmail
individuals, plan terrorist attacks, disseminate false information, defame
individuals, and foment political turmoil. This study describes the history of
deepfake, its development and detection, and the challenges based on
physiological measurements such as eyebrow recognition, eye blinking detection,
eye movement detection, ear and mouth detection, and heartbeat detection. The
study also proposes a scope in this field and compares the different biological
features and their classifiers. Deepfakes are created using the generative
adversarial network (GANs) model, and were once easy to detect by humans due to
visible artifacts. However, as technology has advanced, deepfakes have become
highly indistinguishable from natural images, making it important to review
detection methods.
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