Crisis Management Days

Digital watermarking and blockchain as methods of protecting the authenticity of photos and video content in the fight against deepfake technology

Hadžib Salkić

Bošnjak

Keywords: deepfake, digital watermarking, blockchain, authentication, digital forensics

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Abstract

The modern development of generative technologies, especially deepfake algorithms based on artificial intelligence, poses a serious challenge to the authenticity of digital photos and video content. Traditional protection and verification methods are often insufficient to detect sophisticated manipulations, which requires the introduction of advanced security mechanisms. This paper explores the application of digital watermarking and blockchain technology as complementary methods for ensuring the authenticity and integrity of multimedia content. The methodological approach of the paper is based on the analysis of existing digital watermarking techniques, including visible and invisible watermarks, as well as on the application of blockchain technology to create a decentralized and immutable registry of digital records. Special focus is placed on the integration of these technologies into a single security model that enables tracking the origin of content, verifying authenticity and detecting manipulations. The research results show that the combination of watermarking and blockchain significantly increases the reliability of the protection system, enabling transparency, immutability and cryptographic security of data. It is concluded that such an integrated approach represents an effective solution for combating deepfake content and protecting digital identity in the modern information space.

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References

Hajjej, F., Hamid, M., & Alluhaidan, AS (2026). An integrated framework for proactive deepfake mitigation via attention-driven watermarking and blockchain-based authenticity verification. Scientific Reports .

Alkhatib, M. (2025). A multifaceted deepfake prevention framework integrating watermarking and blockchain. Computers , 14(11), 488.

Faique, M. (2025). Enhancing deepfake detection through blockchain-enabled watermarking. International Journal of Advanced Computer Science and Applications .

Wang, T., et al. (2025). Watermarking for AI content detection: A comprehensive survey. arXiv preprint arXiv:2504.03765 .

Fernando, T., et al. (2025). DeepForgeSeal: Latent space watermarking for deepfake detection. arXiv preprint arXiv:2511.04949 .

Hsu, LY, et al. (2024). AI-assisted deepfake detection using adaptive blind watermarking. Digital Signal Processing .

Nadimpalli, AV, et al. (2024). GAN-based proactive deepfake detection using watermarking. ACM Transactions on Multimedia Computing, Communications, and Applications .

Lan , S., et al. (2024). Facial feature-based dynamic watermarking for deepfake detection. arXiv preprint arXiv:2411.14798 .

Wang, T., et al. (2024). LampMark: Perceptual watermarking for deepfake detection. arXiv preprint arXiv:2411.17209 .

Wang, T., et al. (2025). Fractal watermarking for deepfake detection and localization. arXiv preprint arXiv:2504.09451 .

Verma, S., et al. (2024). Blockchain-enabled deepfake detection using CNN-LSTM models. International Journal of Innovative Research in Computer and Communication Engineering .

International Telecommunication Union (ITU). (2024). AI watermarking and multimedia authenticity standards. Geneva: ITU.

AWESOME. (2025). Blockchain and artificial intelligence in combating deepfake content circulation. Southern Journal of Artificial Intelligence and Blockchain Technologies .

Nguyen, TT, et al. (2022). Deep learning for deepfake detection: A survey. IEEE Transactions on Information Forensics and Security .

Masood, M., et al. (2021). Deepfakes generation and detection: State-of-the-art and challenges. IEEE Access .

Lee, S., et al. (2021). TAR: Generalized forensic framework to detect deepfakes. IEEE Conference on Computer Vision and Pattern Recognition .

Wang, J., et al. (2021). Multi-modal transformers for deepfake detection. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) .

Hadžib Salkić; Nedžad Korajlić; Mahir Zajmović (2025). Digital forensics through practical examples. International Association of Criminal Experts, Bosnia and Herzegovina. Monograph / professional book. ISBN: (in publisher). Total volume: approx. 900 pages.

Hadžib Salkić; Nedžad Korajlić (2025). The comprehensive check of security of information systems through a multidisciplinary approach. Serbian Journal of Engineering Management , Vol. 10, No. 1, pp. 138–153. ISSN: 2217-7153.

Hadžib Salkić; Nedžad Korajlić (2025). Modern approaches to protective measures in corporate security. Quaestus Multidisciplinary Research Journal , pp. 138–153. ISSN: 2284-3456.

Hadžib Salkić; Ismet Kalić; Edin Glogić (2025). Digital forensics in the detection and proof of AI-generated manipulations. Proceedings of the II International Scientific and Research Conference Information Security and Related Cyber Forensic Applications (ISRCFA 2025) , Bosnia and Herzegovina, pp. 221–234.

Hadžib Salkić; Elvedin Zelkanović; Vedad Briga (2025). Detection of an illegal laboratory for the production of synthetic drugs using integrated chemical and digital forensics. Proceedings of the International Conference Forensics, Cybernetics and Artificial Intelligence , pp. 131–145.

Hadžib Salkić; Nedžad Korajlić; Mirza Mustafić (2025). Digital forensics in detecting BEC fraud and money laundering through international financial transactions. Proceedings of the International Conference ISRCFA 2025 , pp. 441–455.

Hadžib Salkić; Mahir Zajmović (2025). Security architectures and privacy on messaging platforms: A comparative analysis of WhatsApp, Viber and Telegram. Proceedings of the International Conference Forensics, Cybernetics and Artificial Intelligence , pp. 515–530.

Hadžib Salkić; Aleksandar Mirojević; Marija Kvasina (2025). Digital trace education: How high school students can learn digital forensics through social media. Proceedings of the International Conference Forensics, Cybernetics and Artificial Intelligence , pp. 554–565 .