梳理生成式AI带来的身份认证挑战与安全威胁
Challenges in GenAI and Authentication: a scoping review
- 系统分析88篇文献，聚焦生成内容的认证难题
- 揭示图像、文本、音频、视频多模态伪造威胁
- 为安全研究提供可参考的漏洞与解决方案图谱
身份认证与真实性自信息共享以来始终是安全挑战，尤其在数字信息背景下更为突出。随着生成式人工智能的发展，这些挑战不断演变，亟需对社会与系统安全的影响进行最新分析。本文通过范围综述方法，分析来自IEEExplorer、Scopus和ACM数据库的88篇文献，围绕六大核心问题展开：相关工作、挑战、攻击面、威胁、现有解决方案及研究空白。最终通过对文献组合的系统性分析，结合个体化评估，一致揭示了图像、文本、音频和视频领域在生成内容真实性方面的关键挑战、缺失环节与潜在风险，为生成式人工智能领域的认证研究提供了坚实基础。
原文摘要 · Abstract (English)
Authentication and authenticity have been a security challenge since the beginning of information sharing, especially in the context of digital information. With the advancement of generative artificial intelligence, these challenges have evolved, demanding a more up-to-date analysis of their impacts on society and system security. This work presents a scoping review that analyzed 88 documents from the IEEExplorer, Scopus, and ACM databases, promoting an analysis of the resulting portfolio through six guiding questions focusing on the most relevant work, challenges, attack surfaces, threats, proposed solutions, and gaps. Finally, the portfolio articles are analyzed through this guiding research lens and also receive individualized analysis. The results consistently outline the challenges, gaps, and threats related to images, text, audio, and video, thereby supporting new research in the areas of authentication and generative artificial intelligence.
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