On large language models safety, security, and privacy: A survey

The integration of artificial intelligence (AI) technology, particularly large language models (LLMs), has become essential across various sectors due to their advanced language comprehension and generation capabilities. Despite their transformative impact in fields such as machine translation and intelligent dialogue systems, LLMs face significant challenges. These challenges include safety, security, and privacy concerns that undermine their trustworthiness and effectiveness, such as hallucinations, backdoor attacks, and privacy leakage. Previous works often conflated safety issues with security concerns. In contrast, our study provides clearer and more reasonable definitions for safety, security, and privacy within the context of LLMs. Building on these definitions, we provide a comprehensive overview of the vulnerabilities and defense mechanisms related to safety, security, and privacy in LLMs. Additionally, we explore the unique research challenges posed by LLMs and suggest potential avenues for future research, aiming to enhance the robustness and reliability of LLMs in the face of emerging threats.