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Recent Advancements in the Field of Deepfake Detection


Affiliations
1 Department of Computer Science, University of Wisconsin-Eau Claire, Eau Claire, Wisconsin, United States
2 Department of Computer Information Science Minnesota State University, Mankato, Mankato, MN, United States
 

A deepfake is a photo or video of a person whose image has been digitally altered or partially replaced with an image of someone else. Deepfakes have the potential to cause a variety of problems and are often used maliciously. A common usage is altering videos of prominent political figures and celebrities. These deepfakes can portray them making offensive, problematic, and/or untrue statements. Current deepfakes can be very realistic, and when used in this way, can spread panic and even influence elections and political opinions. There are many deepfake detection strategies currently in use but finding the most comprehensive and universal method is critical. So, in this survey we will address the problems of malicious deepfake creation and the lack of universal deepfake detection methods. Our objective is to survey and analyze a variety of current methods and advances in the field of deepfake detection.

Keywords

Deepfake, Detection, Neural network, Dataset
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  • Recent Advancements in the Field of Deepfake Detection

Abstract Views: 161  |  PDF Views: 63

Authors

Natalie Krueger
Department of Computer Science, University of Wisconsin-Eau Claire, Eau Claire, Wisconsin, United States
Mounika Vanamala
Department of Computer Science, University of Wisconsin-Eau Claire, Eau Claire, Wisconsin, United States
Rushit Dave
Department of Computer Information Science Minnesota State University, Mankato, Mankato, MN, United States

Abstract


A deepfake is a photo or video of a person whose image has been digitally altered or partially replaced with an image of someone else. Deepfakes have the potential to cause a variety of problems and are often used maliciously. A common usage is altering videos of prominent political figures and celebrities. These deepfakes can portray them making offensive, problematic, and/or untrue statements. Current deepfakes can be very realistic, and when used in this way, can spread panic and even influence elections and political opinions. There are many deepfake detection strategies currently in use but finding the most comprehensive and universal method is critical. So, in this survey we will address the problems of malicious deepfake creation and the lack of universal deepfake detection methods. Our objective is to survey and analyze a variety of current methods and advances in the field of deepfake detection.

Keywords


Deepfake, Detection, Neural network, Dataset

References