2,529+ academic papers on AI security, attacks, and defenses
Showing 181–200 of 212 papers
Clear filtersArth Bhardwaj, Sia Godika, Yuvam Loonker
Traditional, centralized security tools often miss adaptive, multi-vector attacks. We present the Multi-Agent LLM Cyber Defense Framework (MALCDF), a...
Dongchao Zhou, Lingyun Ying, Huajun Chai +1 more
JavaScript's widespread adoption has made it an attractive target for malicious attackers who employ sophisticated obfuscation techniques to conceal...
Amy Chang, Tiffany Saade, Sanket Mendapara +2 more
Artificial intelligence (AI) systems are being readily and rapidly adopted, increasingly permeating critical domains: from consumer platforms and...
Shashie Dilhara Batan Arachchige, Benjamin Zi Hao Zhao, Hassan Jameel Asghar +2 more
Large Language Models (LLMs) are often fine-tuned to adapt their general-purpose knowledge to specific tasks and domains such as cyber threat...
Padmeswari Nandiya, Ahmad Mohsin, Ahmed Ibrahim +2 more
Industry 5.0's increasing integration of IT and OT systems is transforming industrial operations but also expanding the cyber-physical attack...
Jinghao Wang, Ping Zhang, Carter Yagemann
Medical Large Language Models (LLMs) are increasingly deployed for clinical decision support across diverse specialties, yet systematic evaluation of...
Fenghua Weng, Chaochao Lu, Xia Hu +2 more
As multimodal reasoning improves the overall capabilities of Large Vision Language Models (LVLMs), recent studies have begun to explore...
Zhibo Liang, Tianze Hu, Zaiye Chen +1 more
Autonomous Large Language Model (LLM) agents exhibit significant vulnerability to Indirect Prompt Injection (IPI) attacks. These attacks hijack agent...
Saeid Jamshidi, Kawser Wazed Nafi, Arghavan Moradi Dakhel +3 more
The Model Context Protocol (MCP) enables Large Language Models to integrate external tools through structured descriptors, increasing autonomy in...
Arush Sachdeva, Rajendraprasad Saravanan, Gargi Sarkar +2 more
Cybercrime increasingly exploits human cognitive biases in addition to technical vulnerabilities, yet most existing analytical frameworks focus...
Xianzong Wu, Xiaohong Li, Lili Quan +1 more
Large language models(LLMs) are increasingly expanding their real-world applications across domains, e.g., question answering, autonomous driving,...
Yuhang Huang, Junchao Li, Boyang Ma +6 more
Embodied AI systems integrate language models with real world sensing, mobility, and cloud connected mobile apps. Yet while model jailbreaks have...
Zag ElSayed, Craig Erickson, Ernest Pedapati
Healthcare AI systems have historically faced challenges in merging contextual reasoning, long-term state management, and human-verifiable workflows...
M Zeeshan, Saud Satti
Multimodal Artificial Intelligence (AI) systems, particularly Vision-Language Models (VLMs), have become integral to critical applications ranging...
Eranga Bandara, Amin Hass, Ross Gore +8 more
AI agent-based systems are becoming increasingly integral to modern software architectures, enabling autonomous decision-making, dynamic task...
Peter B. Walker, Hannah Davidson, Aiden Foster +3 more
Large Language Models (LLMs) have transformed natural language processing and hold growing promise for advancing science, healthcare, and...
Ruichao Liang, Le Yin, Jing Chen +5 more
LLM-based multi-agent systems (MASs) have reshaped the digital landscape with their emergent coordination and problem-solving capabilities. However,...
Rafflesia Khan, Declan Joyce, Mansura Habiba
The rapid deployment of large language model (LLM)-based agents introduces a new class of risks, driven by their capacity for autonomous planning,...
Mihai Christodorescu, Earlence Fernandes, Ashish Hooda +11 more
In recent years, agentic artificial intelligence (AI) systems are becoming increasingly widespread. These systems allow agents to use various tools,...
Kaixiang Wang, Zhaojiacheng Zhou, Bunyod Suvonov +2 more
Large Language Model (LLM)-based Multi-Agent Systems (MAS) are susceptible to linguistic attacks that can trigger cascading failures across the...
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