SecureGenAI: A Standardized Framework for Authentication and Provenance in AI-Generated Images using Blockchain-Enhanced Watermarking
Dinesh Besiahgari · 2025
The escalating popularity of Generative AI (GenAI) for image creation has raised challenges surrounding authenticity, ownership, and misuse. This paper proposes SecureGenAI, a revolutionary framework designed to tackle those issues, which incorporates invisible watermarks into the genesis of the images produced by the AI model to allow for seamless verification that is tamper-proof. SecureGenAI contrasts with more traditional methods based on watermarking, which usually add a watermark to an image after it has been created. SecureGenAI implements Discrete Wavelet Transform (DWT) watermarking in the AI model itself, allowing for greater resistance to adversarial techniques used to remove watermarks after image generation. Moreover, the framework combines the advantages of DWT watermarking with blockchain to store and authenticate the watermark data, making sure that watermarks cannot be altered or their identifying information removed. One of the standout features of SecureGenAI is the real-time API designed for online image verification: it eliminates the need for verification metadata, which can be easily spoofed. This shift in paradigm increases the trustworthiness, accountability and security of AI generated content while lowering risks of being targeted by deepfakes or image manipulation. SecureGenAI’s combination of embedded invisible watermarking in the AI model and decentralized blockchain-enabled verification presents a new technological advantage for the field of AI-generated imagery.