2,560+ academic papers on AI security, attacks, and defenses
Showing 181–200 of 1,220 papers
Clear filtersSimon Calderon, Niklas Johansson, Onur Günlü
Ensuring ciphertext indistinguishability is fundamental to cryptographic security, but empirically validating this property in real implementations...
Nikolaos D. Tantaroudas, Ilias Karachalios, Andrew J. McCracken
The field of cybersecurity is confronted with two interrelated challenges: a worldwide deficit of qualified practitioners and ongoing human-factor...
Yinghan Hou, Zongyou Yang
OpenClaw's ClawHub marketplace hosts over 13,000 community-contributed agent skills, and between 13% and 26% of them contain security vulnerabilities...
Peigui Qi, Kunsheng Tang, Yanpu Yu +7 more
Vision-Language Models (VLMs) face significant safety vulnerabilities from malicious prompt attacks due to weakened alignment during visual...
Mutsumi Sasaki, Kouta Nakayama, Yusuke Miyao +2 more
When introducing Large Language Models (LLMs) into industrial applications, such as healthcare and education, the risk of generating harmful content...
Nirajan Acharya, Gaurav Kumar Gupta
The Model Context Protocol (MCP), introduced by Anthropic in November 2024 and now governed by the Linux Foundation's Agentic AI Foundation, has...
Xaver Fink, Borja Fernandez Adiego, Daniele Mirarchi +4 more
In this paper, we analyze and improve the adversarial robustness of a convolutional neural network (CNN) that assists crystal-collimator alignment at...
Igor Maljkovic, Maria Rosaria Briglia, Iacopo Masi +2 more
Vision-Language Models (VLMs) have become essential for tasks such as image synthesis, captioning, and retrieval by aligning textual and visual...
Jiaren Peng, Zeqin Li, Chang You +17 more
The rapid advancement of Large Language Models (LLMs) has created new opportunities for Automated Penetration Testing (AutoPT), spawning numerous...
Shaofei Huang, Christopher M. Poskitt, Lwin Khin Shar
Cyber-physical systems often contend with incomplete architectural documentation or outdated information resulting from legacy technologies,...
Md Shamimul Islam, Luis G. Jaimes, Ayesha S. Dina
Network Intrusion Detection Systems (NIDS) face important limitations. Signature-based methods are effective for known attack patterns, but they...
Anes Abdennebi, Nadjia Kara, Laaziz Lahlou +1 more
Modern Security Operations Centers struggle with alert fatigue, fragmented tooling, and limited cross-source event correlation. Challenges that...
Wuyang Zhang, Shichao Pei
Tool-use large language model (LLM) agents are increasingly deployed to support sensitive workflows, relying on tool calls for retrieval, external...
Purva Chiniya, Kevin Scaria, Sagar Chaturvedi
Large language models (LLMs) remain susceptible to jailbreak and direct prompt-injection attacks, yet the strongest defensive filters frequently...
Geert Trooskens, Aaron Karlsberg, Anmol Sharma +6 more
We study compiled AI, a paradigm in which large language models generate executable code artifacts during a compilation phase, after which workflows...
Jiling Zhou, Aisvarya Adeseye, Seppo Virtanen +2 more
Chain-of-Thought (CoT) prompting has been used to enhance the reasoning capability of LLMs. However, its reliability in security-sensitive analytical...
Zijun Wang, Haoqin Tu, Letian Zhang +11 more
OpenClaw, the most widely deployed personal AI agent in early 2026, operates with full local system access and integrates with sensitive services...
Vinod Vaikuntanathan, Or Zamir
AI agents are increasingly deployed to interact with other agents on behalf of users and organizations. We ask whether two such agents, operated by...
Zhuohao Yu, Zhiwei Steven Wu, Adam Block
Inference-time compute scaling has emerged as a powerful paradigm for improving language model performance on a wide range of tasks, but the question...
Jia Chengyu, AprilPyone MaungMaung, Huy H. Nguyen +2 more
Recent advances in vision-language models (VLMs) trained on web-scale image-text pairs have enabled impressive zero-shot transfer across a diverse...
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