2,583+ academic papers on AI security, attacks, and defenses
Showing 341–360 of 890 papers
Clear filtersMinbeom Kim, Mihir Parmar, Phillip Wallis +5 more
AI agents equipped with tool-calling capabilities are susceptible to Indirect Prompt Injection (IPI) attacks. In this attack scenario, malicious...
Tianyi Wang, Huawei Fan, Yuanchao Shu +2 more
Large Language Models face an emerging and critical threat known as latency attacks. Because LLM inference is inherently expensive, even modest...
Yuhao Wang, Shengfang Zhai, Guanghao Jin +3 more
Large Language Model (LLM)-based agents employ external and internal memory systems to handle complex, goal-oriented tasks, yet this exposes them to...
Tianyi Wu, Mingzhe Du, Yue Liu +4 more
Large language models (LLMs) are increasingly used in software development, yet their tendency to generate insecure code remains a major barrier to...
Abdullah Arafat Miah, Kevin Vu, Yu Bi
Spiking Neural Networks (SNNs) are energy-efficient counterparts of Deep Neural Networks (DNNs) with high biological plausibility, as information is...
Shang Liu, Hanyu Pei, Zeyan Liu
Large Language Models(LLMs) have been successful in numerous fields. Alignment has usually been applied to prevent them from harmful purposes....
Zhuoheng Li, Ying Chen
Multimodal large language models (MLLMs) have advanced the capabilities to interpret and act on visual input in 3D environments, empowering diverse...
Mingqian Feng, Xiaodong Liu, Weiwei Yang +4 more
Multi-turn jailbreaks capture the real threat model for safety-aligned chatbots, where single-turn attacks are merely a special case. Yet existing...
Yassine Chagna, Antal Goldschmidt
This project explores large language models (LLMs) for anomaly detection across heterogeneous log sources. Traditional intrusion detection systems...
Ying Song, Balaji Palanisamy
Graph-structured data underpin a wide spectrum of modern applications. However, complex graph topologies and homophilic patterns can facilitate...
Li Lu, Yanjie Zhao, Hongzhou Rao +2 more
Large Language Models (LLMs) have demonstrated remarkable proficiency in vulnerability detection. However, a critical reliability gap persists:...
Mengyao Du, Han Fang, Haokai Ma +4 more
Suffix-based jailbreak attacks append an adversarial suffix, i.e., a short token sequence, to steer aligned LLMs into unsafe outputs. Since suffixes...
Haipeng Li, Rongxuan Peng, Anwei Luo +3 more
The rapid advancement of AI-Generated Content (AIGC) technologies poses significant challenges for authenticity assessment. However, existing...
Minkyoo Song, Jaehan Kim, Myungchul Kang +3 more
Graph-based retrieval-augmented generation (Graph RAG) is increasingly deployed to support LLM applications by augmenting user queries with...
Sung-Hoon Yoon, Ruizhi Qian, Minda Zhao +2 more
Large Language Models (LLMs) have become integral to many domains, making their safety a critical priority. Prior jailbreaking research has explored...
Junhyeok Lee, Han Jang, Kyu Sung Choi
Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) systems are increasingly integrated into clinical workflows; however, prompt...
Xin Chen, Jie Zhang, Florian Tramèr
Prompt injection is one of the most critical vulnerabilities in LLM agents; yet, effective automated attacks remain largely unexplored from an...
Takashi Koide, Hiroki Nakano, Daiki Chiba
Phishing sites continue to grow in volume and sophistication. Recent work leverages large language models (LLMs) to analyze URLs, HTML, and rendered...
Yao Zhou, Zeen Song, Wenwen Qiang +4 more
Safety alignment mechanisms in Large Language Models (LLMs) often operate as latent internal states, obscuring the model's inherent capabilities....
Zihan Wang, Hongwei Li, Rui Zhang +2 more
Chat template is a common technique used in the training and inference stages of Large Language Models (LLMs). It can transform input and output data...
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