Abstract

With the widespread adoption of Large Language Models (LLMs), security traceability, copyright protection, and compliance regulation of their generated content have become critical issues requiring urgent resolution. While LLM watermarking technology holds promise for addressing these issues, existing research primarily focuses on theoretical construction in general scenarios, lacking adaptability exploration for vertical industries. Specifically, current methods struggle to handle challenges unique to e-commerce scenarios, such as high-frequency model invocation, data privacy protection, and complex permission management. To address this, this paper summarizes and refines a framework for cryptography-based LLM watermarking schemes and deeply explores their application practices in the e-commerce field. Addressing urgent needs in the e-commerce environment—such as copyright protection for product descriptions, traceability of intelligent customer service dialogues, and compliance of generated content—we designed adaptable watermark embedding and verification mechanisms respectively. The proposed scheme leverages cryptographic primitives to achieve fine-grained permission management and identity verification, overcoming the limitations of traditional general-purpose watermarking applications which lack specificity. Through scenario simulations and functional evaluations, we demonstrate the engineering feasibility and robustness of cryptographic watermarking in complex e-commerce businesses. This study offers novel technical insights for cryptography applications in e-commerce oriented towards the AI era. It is expected to facilitate the secure deployment of AI technology in e-commerce scenarios and provides new technical paths and practical references for building a trustworthy AI e-commerce ecosystem.

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