# Deepfake Technology Unveiled: The Commoditization of AI and Its Impact on Digital Trust

arXiv: https://arxiv.org/abs/2506.07363 · HTML: https://mlsanity.com/paper/2506.07363/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 5 of its 38 references that are in the map.
- First posted on arXiv 24 Jan 2025.

## Builds on (most cited first, 5 of 5)

- [Generating Long Videos of Dynamic Scenes](https://mlsanity.com/paper/2206.03429/) (2022)
- [NeuWigs: A Neural Dynamic Model for Volumetric Hair Capture and Animation](https://mlsanity.com/paper/2212.00613/) (2022)
- [V2A-Mark: Versatile Deep Visual-Audio Watermarking for Manipulation Localization and Copyright Protection](https://mlsanity.com/paper/2404.16824/) (2024)
- [Fake News, Disinformation, and Deepfakes: Leveraging Distributed Ledger Technologies and Blockchain to Combat Digital Deception and Counterfeit Reality](https://mlsanity.com/paper/1904.05386/) (2019)
- [Discussion Paper: The Threat of Real Time Deepfakes](https://mlsanity.com/paper/2306.02487/) (2023)

## Built on by (most cited first, 2 of 2)

- [Immune2V: Image Immunization Against Dual-Stream Image-to-Video Generation](https://mlsanity.com/paper/2604.10837/) (2026)
- [GRRE: Leveraging G-Channel Removed Reconstruction Error for Robust Detection of AI-Generated Images](https://mlsanity.com/paper/2601.02709/) (2026)

## Abstract (arXiv)

Deepfake Technology Unveiled: The Commoditization of AI and Its Impact on Digital Trust. With the increasing accessibility of generative AI, tools for voice cloning, face-swapping, and synthetic media creation have advanced significantly, lowering both financial and technical barriers for their use. While these technologies present innovative opportunities, their rapid growth raises concerns about trust, privacy, and security. This white paper explores the implications of deepfake technology, analyzing its role in enabling fraud, misinformation, and the erosion of authenticity in multimedia. Using cost-effective, easy to use tools such as Runway, Rope, and ElevenLabs, we explore how realistic deepfakes can be created with limited resources, demonstrating the risks posed to individuals and organizations alike. By analyzing the technical and ethical challenges of deepfake mitigation and detection, we emphasize the urgent need for regulatory frameworks, public awareness, and collaborative efforts to maintain trust in digital media.