Toward Trustworthy Governance of AI-Generated Content (AIGC): A Blockchain-Driven Regulatory Framework for Secure Digital Ecosystems

【Author】 Yang, Fan; Abedin, Mohammad Zoynul; Qiao, Yanan; Ye, Lvyang

【Source】IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT

【影响因子】8.702

【Abstract】Digital platforms are experiencing a growing presence of generative artificial intelligence (AI) content, raising concerns due to the prevalence of misinformation that disrupts market integrity. Consequently, the development of effective regulatory measures for overseeing generative AI content becomes imperative. This necessitates the establishment of mechanisms to detect and filter out inaccuracies, ensuring compliance with regulatory requirements. In addition, collaboration among experts, regulators, and AI developers is essential to encourage responsible AI deployment on digital platforms. Successful governance hinges on principles of transparency, accountability, and proactive risk management to navigate the evolving generative AI on digital platforms. Therefore, in order to address the security issues currently faced by artificial intelligence generated content (AIGC), this article first proposes a method of efficient cache mechanism for AIGC content. The secure method of determining the identity of AIGC content owners is proposed based on blockchain technology. Subsequently, it suggests mechanisms for access control and data encryption for generated content within a blockchain environment. Finally, it presents an efficient data supervision mechanism tailored to the AIGC environment. The methods outlined in this article aim to enhance security from three perspectives: protection of content creators' identities, safeguarding data security, and ensuring effective data supervision within the AIGC framework. The experimental results further confirm that our proposed method not only ensures the security of the AIGC framework but also provides an efficient data analysis and supervision solution for digital platforms.

【Keywords】Artificial intelligence generated content (AIGC) regulation; blockchain governance; consensus mechanism; data security; data traceability; Artificial intelligence generated content (AIGC) regulation; blockchain governance; consensus mechanism; data security; data traceability

【发表时间】2024

【收录时间】2024-10-28

【文献类型】理论模型

【主题类别】

区块链技术-核心技术-身份验证