The Cybersecurity Crisis of Artificial Intelligence: Unrestrained Adoption and Natural Language-Based Attacks
This addresses cybersecurity risks for users and developers of AI systems, but it is incremental as it focuses on analyzing known vulnerabilities rather than introducing new solutions.
The paper tackles the cybersecurity vulnerabilities introduced by the widespread adoption of autoregressive large language models (AR-LLMs) like ChatGPT, analyzing how natural language serves as an attack vector and proposing recommendations to mitigate these challenges, but it does not provide concrete numerical results.
The widespread integration of autoregressive-large language models (AR-LLMs), such as ChatGPT, across established applications, like search engines, has introduced critical vulnerabilities with uniquely scalable characteristics. In this commentary, we analyse these vulnerabilities, their dependence on natural language as a vector of attack, and their challenges to cybersecurity best practices. We offer recommendations designed to mitigate these challenges.