Abstract: Deepfake technology poses a growing threat to the authenticity and trustworthiness of digital media, necessitating the development of advanced detection mechanisms. While AI-based methods have shown promise, they generally face limitations in terms of generalization and scalability. We present a blockchain-enabled watermarking technique, characterized by its immutable, transparent, and decentralized nature, which offers a robust complementary approach for enhancing media authentication through methods such as cryptographic watermarking, decentralized identity, and content provenance tracking. To train and evaluate blockchain-based watermarking and deepfake detection systems, a variety of large-scale datasets are utilized. Video datasets include UADFV (49 real, 49 fake), Deepfake-TIMIT (320 real, 640 fake), DFFD (1000 real, 3000 fake), Celeb-DF v2 (590 real, 5639 fake), DFDC (23,564 real, 104,500 fake), DeeperForensics-1.0 (50,000 real, 10,000 fake), FaceForensics++ (1000 real, 5000 fake), and ForgeryNet (99,630 real, 121,617 fake). Image datasets include DFFD (58,703 real, 240,336 fake), FFHQ (70,000 GAN-generated), iFakeFaceDB (87,000 fake), 100k AI Faces, and over 2.8 million samples in ForgeryNet. Despite integration challenges such as scalability, computational cost, and standardization, blockchain-based solutions show promise in tracking content origin and enhancing verification. Simulation results demonstrate that the proposed blockchain-enabled watermarking achieves a higher accuracy in detecting fake content compared to existing machine learning methods.

Qurat-ul-Ain Mastoi, Muhammad Faisal Memon, Salman Jan, Atif Jamil, Muhammad Faique, Zeeshan Ali, Abdullah Lakhan and Toqeer Ali Syed. “Enhancing Deepfake Content Detection Through Blockchain Technology”. International Journal of Advanced Computer Science and Applications (IJACSA) 16.6 (2025). http://dx.doi.org/10.14569/IJACSA.2025.0160607

@article{Mastoi2025,
title = {Enhancing Deepfake Content Detection Through Blockchain Technology},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2025.0160607},
url = {http://dx.doi.org/10.14569/IJACSA.2025.0160607},
year = {2025},
publisher = {The Science and Information Organization},
volume = {16},
number = {6},
author = {Qurat-ul-Ain Mastoi and Muhammad Faisal Memon and Salman Jan and Atif Jamil and Muhammad Faique and Zeeshan Ali and Abdullah Lakhan and Toqeer Ali Syed}
}