Security and privacy challenges of large language models: A survey

BC Das, MH Amini, Y Wu - ACM Computing Surveys, 2025 - dl.acm.org
Large language models (LLMs) have demonstrated extraordinary capabilities and
contributed to multiple fields, such as generating and summarizing text, language …

[HTML][HTML] A survey on large language model (llm) security and privacy: The good, the bad, and the ugly

Y Yao, J Duan, K Xu, Y Cai, Z Sun, Y Zhang - High-Confidence Computing, 2024 - Elsevier
Abstract Large Language Models (LLMs), such as ChatGPT and Bard, have revolutionized
natural language understanding and generation. They possess deep language …

Unleashing the potential of prompt engineering in large language models: a comprehensive review

B Chen, Z Zhang, N Langrené, S Zhu - arxiv preprint arxiv:2310.14735, 2023 - arxiv.org
This comprehensive review delves into the pivotal role of prompt engineering in unleashing
the capabilities of Large Language Models (LLMs). The development of Artificial Intelligence …

Foundational challenges in assuring alignment and safety of large language models

U Anwar, A Saparov, J Rando, D Paleka… - arxiv preprint arxiv …, 2024 - arxiv.org
This work identifies 18 foundational challenges in assuring the alignment and safety of large
language models (LLMs). These challenges are organized into three different categories …

Deepinception: Hypnotize large language model to be jailbreaker

X Li, Z Zhou, J Zhu, J Yao, T Liu, B Han - arxiv preprint arxiv:2311.03191, 2023 - arxiv.org
Despite remarkable success in various applications, large language models (LLMs) are
vulnerable to adversarial jailbreaks that make the safety guardrails void. However, previous …

Black-box access is insufficient for rigorous ai audits

S Casper, C Ezell, C Siegmann, N Kolt… - Proceedings of the …, 2024 - dl.acm.org
External audits of AI systems are increasingly recognized as a key mechanism for AI
governance. The effectiveness of an audit, however, depends on the degree of access …

Adashield: Safeguarding multimodal large language models from structure-based attack via adaptive shield prompting

Y Wang, X Liu, Y Li, M Chen, C **ao - European Conference on Computer …, 2024 - Springer
With the advent and widespread deployment of Multimodal Large Language Models
(MLLMs), the imperative to ensure their safety has become increasingly pronounced …

A survey on the memory mechanism of large language model based agents

Z Zhang, X Bo, C Ma, R Li, X Chen, Q Dai, J Zhu… - arxiv preprint arxiv …, 2024 - arxiv.org
Large language model (LLM) based agents have recently attracted much attention from the
research and industry communities. Compared with original LLMs, LLM-based agents are …

On protecting the data privacy of large language models (llms): A survey

B Yan, K Li, M Xu, Y Dong, Y Zhang, Z Ren… - arxiv preprint arxiv …, 2024 - arxiv.org
Large language models (LLMs) are complex artificial intelligence systems capable of
understanding, generating and translating human language. They learn language patterns …

A survey of graph meets large language model: Progress and future directions

Y Li, Z Li, P Wang, J Li, X Sun, H Cheng… - arxiv preprint arxiv …, 2023 - arxiv.org
Graph plays a significant role in representing and analyzing complex relationships in real-
world applications such as citation networks, social networks, and biological data. Recently …