2,560+ academic papers on AI security, attacks, and defenses
Showing 301–320 of 635 papers
Clear filtersJivnesh Sandhan, Fei Cheng, Tushar Sandhan +1 more
Large Language Models (LLMs) are increasingly deployed in domains such as education, mental health and customer support, where stable and consistent...
Fengheng Chu, Jiahao Chen, Yuhong Wang +4 more
While Large Language Models (LLMs) are aligned to mitigate risks, their safety guardrails remain fragile against jailbreak attacks. This reveals...
Mingyu Yu, Lana Liu, Zhehao Zhao +2 more
The rapid advancement of Multimodal Large Language Models (MLLMs) has introduced complex security challenges, particularly at the intersection of...
Md Nabi Newaz Khan, Abdullah Arafat Miah, Yu Bi
Graph neural network (GNN) have demonstrated exceptional performance in solving critical problems across diverse domains yet remain susceptible to...
Sahar Tahmasebi, Eric Müller-Budack, Ralph Ewerth
Misinformation and fake news have become a pressing societal challenge, driving the need for reliable automated detection methods. Prior research has...
Piyumi Bhagya Sudasinghe, Kushan Sudheera Kalupahana Liyanage, Harsha S. Gardiyawasam Pussewalage
The rapid growth of Internet of Things (IoT) devices has increased the scale and diversity of cyberattacks, exposing limitations in traditional...
Zhihao Chen, Zirui Gong, Jianting Ning +2 more
Federated Rank Learning (FRL) is a promising Federated Learning (FL) paradigm designed to be resilient against model poisoning attacks due to its...
Mohammad Shamim Ahsan, Peng Liu
In the network security domain, due to practical issues -- including imbalanced data and heterogeneous legitimate network traffic -- adversarial...
Zhihao Dou, Dongfei Cui, Weida Wang +7 more
Split Learning (SL) offers a framework for collaborative model training that respects data privacy by allowing participants to share the same dataset...
Jiani Liu, Yixin He, Lanlan Fan +5 more
Navigation agents powered by large language models (LLMs) convert natural language instructions into executable plans and actions. Compared to...
Bingxin Xu, Yuzhang Shang, Binghui Wang +1 more
Vision-Language-Action (VLA) models are increasingly deployed in safety-critical robotic applications, yet their security vulnerabilities remain...
Asen Dotsinski, Panagiotis Eustratiadis
As open-weight large language models (LLMs) increase in capabilities, safeguarding them against malicious prompts and understanding possible attack...
Diego Gosmar, Deborah A. Dahl
Prompt injection remains a central obstacle to the safe deployment of large language models, particularly in multi-agent settings where intermediate...
Xiaolei Zhang, Xiaojun Jia, Liquan Chen +1 more
Introducing reasoning models into Retrieval-Augmented Generation (RAG) systems enhances task performance through step-by-step reasoning, logical...
Jesus-German Ortiz-Barajas, Jonathan Tonglet, Vivek Gupta +1 more
Multimodal large language models (MLLMs) are increasingly used to automate chart generation from data tables, enabling efficient data analysis and...
Zhixin Xie, Xurui Song, Jun Luo
The demand of customized large language models (LLMs) has led to commercial LLMs offering black-box fine-tuning APIs, yet this convenience introduces...
Anirudh Sekar, Mrinal Agarwal, Rachel Sharma +4 more
Prompt injection attacks have become an increasing vulnerability for LLM applications, where adversarial prompts exploit indirect input channels such...
Aiman Al Masoud, Marco Arazzi, Antonino Nocera
Retrieval-Augmented Generation (RAG) has attracted significant attention due to its ability to combine the generative capabilities of Large Language...
Yipu Dou, Wang Yang
Large language model (LLM) safety evaluation is moving from content moderation to action security as modern systems gain persistent state, tool...
Chetan Pathade, Vinod Dhimam, Sheheryar Ahmad +1 more
Serverless computing has achieved widespread adoption, with over 70% of AWS organizations using serverless solutions [1]. Meanwhile, machine learning...
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