Challenges in GenAI and Authentication: a scoping review

TL;DR

This paper provides a comprehensive review of the evolving challenges, threats, and gaps in authentication related to generative AI across various media types, highlighting areas for future research.

Contribution

It offers a systematic scoping review of 88 documents, identifying key challenges, attack surfaces, threats, and solutions in the context of generative AI and authentication.

Findings

Challenges in image, text, audio, and video authentication

Identification of gaps and threats in generative AI security

Analysis of proposed solutions and research gaps

Abstract

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.