Intelligent Generation and Security Protection for IP Digital Assets: Key Technologies and Teaching-Oriented Practice

Abstract

With the rapid proliferation of artificial intelligence generated content (AIGC), non‑fungible tokens (NFTs), and blockchain‑based services, creative works are increasingly born digital and managed as intellectual property (IP) digital assets. However, the assetization of content has outpaced the maturity of the supporting legal, technical, and educational infrastructures. Content creators and learners face fragmented tools for creation, registration, traceability, and infringement detection, which leads to weak evidence chains and high transaction costs in rights protection. This paper proposes an integrated framework for intelligent generation and security protection of IP digital assets that tightly couples AIGC engines with multi‑modal watermarking, blockchain‑based registration, and privacy‑preserving analytics. On this basis, a teaching‑oriented implementation is designed and deployed in a university course on digital media and IP management. The system supports full‑lifecycle management of images, text, code, and multimedia works, enabling students to experience rights creation, proof‑of‑ownership, risk diagnosis, and evidence preservation in realistic project tasks. Experimental results on a mixed benchmark of 4,200 assets show that the proposed scheme improves watermark robustness by 7.5% on average and shortens rights registration latency by 68% compared with traditional workflows, while significantly enhancing students’ IP literacy and compliance intention. The study demonstrates that IP digital‑asset technology can be transformed from a purely legal or technical topic into an operational teaching infrastructure, supporting both innovation and compliance in the AIGC era.