A comprehensive overview of Deepfake: Generation, detection, datasets, and opportunities

Abstract

When used maliciously, deepfake can pose detrimental implications to political and social forces including reducing public trust in institutions, damaging the reputation of prominent individuals, and influencing public opinions. As there is currently no specific law to address deepfakes, thus deepfake detection, which is an action to discriminate pristine media from deepfake media, plays a vital role in identifying and thwarting deepfake. This paper provides readers with a comprehensive and easy-to-understand state-of-the-art related to deepfake generation and detection. Specifically, we provide a synthesized overview and recent progress in deepfakes by categorizing our review into deepfake generation and detection. We underline publicly available deepfake generation tools and datasets for benchmarking. We also provide research insights, discuss existing gaps, and present trends for future research to facilitate the development of deepfake research.