With the widespread use of large artificial intelligence (AI) models such as ChatGPT, AI-generated content (AIGC) has garnered increasing attention and is leading a paradigm shift in content creation and knowledge representation. AIGC uses generative large AI algorithms to assist or replace humans in creating massive, high-quality, and human-like content at a faster pace and lower cost, based on user-provided prompts. Despite the recent significant progress in AIGC, security, privacy, ethical, and legal challenges still need to be addressed. This paper presents an in-depth survey of working principles, security and privacy threats, state-of-the-art solutions, and future challenges of the AIGC paradigm. Specifically, we first explore the enabling technologies, general architecture of AIGC, and discuss its working modes and key characteristics. Then, we investigate the taxonomy of security and privacy threats to AIGC and highlight the ethical and societal implications of GPT and AIGC technologies. Furthermore, we review the state-of-the-art AIGC watermarking approaches for regulatable AIGC paradigms regarding the AIGC model and its produced content. Finally, we identify future challenges and open research directions related to AIGC.

翻译：随着ChatGPT等大规模人工智能（AI）模型的广泛应用，AI生成内容（AIGC）日益受到关注，正引领内容创作与知识表征的模式转变。AIGC利用生成式大规模AI算法，基于用户提示，以更快速度和更低成本辅助或替代人类创作海量、高质量且拟人化的内容。尽管AIGC近期取得了重大进展，但安全、隐私、伦理及法律挑战仍有待解决。本文对AIGC范式的工作原理、安全与隐私威胁、前沿解决方案及未来挑战进行了深入综述。具体而言，我们首先探讨了AIGC的使能技术与通用架构，并分析其工作模式与关键特性。随后，我们研究了AIGC面临的安全与隐私威胁分类，并强调了GPT与AIGC技术的伦理与社会影响。此外，我们针对AIGC模型及其生成内容，综述了用于可监管AIGC范式的前沿水印技术。最后，我们指出了与AIGC相关的未来挑战与开放研究方向。