# The Emerging Threats of Deepfake Attacks and Countermeasures

arXiv: https://arxiv.org/abs/2012.07989 · HTML: https://mlsanity.com/paper/2012.07989/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 14 Dec 2020.

## Built on by (most cited first, 5 of 5)

- [Seeing is Living? Rethinking the Security of Facial Liveness Verification in the Deepfake Era](https://mlsanity.com/paper/2202.10673/) (2022)
- [XAttnMark: Learning Robust Audio Watermarking with Cross-Attention](https://mlsanity.com/paper/2502.04230/) (2025)
- [LLMs unlock new paths to monetizing exploits](https://mlsanity.com/paper/2505.11449/) (2025)
- [Creation and Detection of German Voice Deepfakes](https://mlsanity.com/paper/2108.01469/) (2021)
- [SpectraNet: FFT-assisted Deep Learning Classifier for Deepfake Face Detection](https://mlsanity.com/paper/2511.19187/) (2025)

## Abstract (arXiv)

Deepfake technology (DT) has taken a new level of sophistication. Cybercriminals now can manipulate sounds, images, and videos to defraud and misinform individuals and businesses. This represents a growing threat to international institutions and individuals which needs to be addressed. This paper provides an overview of deepfakes, their benefits to society, and how DT works. Highlights the threats that are presented by deepfakes to businesses, politics, and judicial systems worldwide. Additionally, the paper will explore potential solutions to deepfakes and conclude with future research direction.