Beyond protection: Unveiling neural network copyright trading

The advent of deep learning has transformed data into invaluable intellectual property, encapsulated within trained neural network models. While copyright protection mechanisms exist, the lack of a secure, standardized platform for trading these intellectual assets limits their commercial potential. This study introduces a blockchain-based framework designed to invigorate the trading ecosystem for neural network model copyrights. A key innovation is our advanced watermarking technique, specifically developed for neural networks. This method embeds copyright information directly into the model architecture during training, providing robust protection against unauthorized use and modifications. Additionally, we have developed a decentralized blockchain marketplace tailored for the peer-to-peer exchange of authenticated model copyrights. This platform utilizes smart contracts to ensure secure, seamless copyright ownership transfers, enabling fluid exchanges within a trustless environment. By integrating cutting-edge watermarking technology with a decentralized trading venue, our framework establishes a market infrastructure that treats neural network models as a new class of freely tradable digital assets, thereby accelerating AI innovation and adoption across various sectors.