Discussion Paper: The Threat of Real Time Deepfakes
This is an incremental discussion paper that highlights a societal problem for the general public and security professionals, focusing on the risks of real-time deepfake technology.
The paper addresses the emerging threat of real-time deepfakes, which are generated by advanced generative models to impersonate individuals for malicious purposes like misinformation and fraud, and it discusses implications, challenges, and suggests research directions for stronger defenses.
Generative deep learning models are able to create realistic audio and video. This technology has been used to impersonate the faces and voices of individuals. These ``deepfakes'' are being used to spread misinformation, enable scams, perform fraud, and blackmail the innocent. The technology continues to advance and today attackers have the ability to generate deepfakes in real-time. This new capability poses a significant threat to society as attackers begin to exploit the technology in advances social engineering attacks. In this paper, we discuss the implications of this emerging threat, identify the challenges with preventing these attacks and suggest a better direction for researching stronger defences.