Title

Panel E: What You See Is Not What You Know: Deepfake Image Manipulation

Presenter Information

Cathryn AllenFollow

Faculty Mentor(s)

Dr. Bryson Payne, Dr. Chuck Robertson, Dr. Tamirat Abegaz, Dr. Royce Dansby-Sparks

Campus

Dahlonega

Proposal Type

Oral Presentation

Subject Area

Computer Science

Location

Nesbitt 3212

Start Date

25-3-2022 11:00 AM

End Date

25-3-2022 12:00 PM

Description/Abstract

Social media is becoming a large part of people's lives. What is posted online is quickly believed by those who view it. This is due to the many psychological components that cause people to accept information as truth. Because of this, deepfakes pose a potential online threat. Deepfakes are videos that have been altered from their original form by swapping faces, changing audio, or any other change made to the video that manipulates the meaning. Deepfakes can range from being lighthearted to being deceitful and containing misinformation, information that is not true. The deceitful videos are known to spread rapidly online and influence people's opinions and ideas. This study was designed to learn more about deepfakes by analyzing people's ability to determine if videos are deepfakes. The researcher created deepfake videos by using DeepFaceLab, a GitHub deepfake software. A survey was put together consisting of deepfake videos and original unedited videos. The participants had to view the videos and determine if the videos shown were deepfakes or originals. They also provided their confidence with their answer. The survey fluctuated the familiarity that the viewers had with the subjects of the videos, by occasionally providing photos of the subjects. Also, the number of videos shown at one time was manipulated. This survey helped to provide information on what creates more deceptive deepfakes, what could potentially counter a deepfake, and how well people discover deepfakes.

Media Format

flash_audio

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Mar 25th, 11:00 AM Mar 25th, 12:00 PM

Panel E: What You See Is Not What You Know: Deepfake Image Manipulation

Nesbitt 3212

Social media is becoming a large part of people's lives. What is posted online is quickly believed by those who view it. This is due to the many psychological components that cause people to accept information as truth. Because of this, deepfakes pose a potential online threat. Deepfakes are videos that have been altered from their original form by swapping faces, changing audio, or any other change made to the video that manipulates the meaning. Deepfakes can range from being lighthearted to being deceitful and containing misinformation, information that is not true. The deceitful videos are known to spread rapidly online and influence people's opinions and ideas. This study was designed to learn more about deepfakes by analyzing people's ability to determine if videos are deepfakes. The researcher created deepfake videos by using DeepFaceLab, a GitHub deepfake software. A survey was put together consisting of deepfake videos and original unedited videos. The participants had to view the videos and determine if the videos shown were deepfakes or originals. They also provided their confidence with their answer. The survey fluctuated the familiarity that the viewers had with the subjects of the videos, by occasionally providing photos of the subjects. Also, the number of videos shown at one time was manipulated. This survey helped to provide information on what creates more deceptive deepfakes, what could potentially counter a deepfake, and how well people discover deepfakes.