2,529+ academic papers on AI security, attacks, and defenses
Showing 121–140 of 919 papers
Clear filtersHailin Liu, Eugene Ilyushin, Jie Ni +1 more
Large language model (LLM) agents are vulnerable to prompt-injection attacks that propagate through multi-step workflows, tool interactions, and...
Jianming Tong, Hanshen Xiao, Krishna Kumar Nair +5 more
Multi-user virtual reality enables immersive interaction. However, rendering avatars for numerous participants on each headset incurs prohibitive...
Dongwook Lee, Eunwoo Song, Che Hyun Lee +2 more
While recent Spoken Language Models (SLMs) have been actively deployed in real-world scenarios, they lack the capability to discern Third-Party...
Rina Mishra, Gaurav Varshney, Doddipatla Sesha Sahithi
The rapid adoption of open-source Large Language Models (LLMs) in offline and enterprise environments has introduced a largely unexamined security...
XiangRui Zhang, Qiang Li, Haining Wang
Binary analysis increasingly relies on large language models (LLMs) to perform semantic reasoning over complex program behaviors. However, existing...
Xuanli He, Bilgehan Sel, Faizan Ali +3 more
Large Language Models (LLMs) are increasingly exposed to adaptive jailbreaking, particularly in high-stakes Chemical, Biological, Radiological, and...
Firas Ben Hmida, Philemon Hailemariam, Kashif Ali Khan +1 more
Deep neural networks (DNNs) remain largely opaque at inference time, limiting our ability to detect and diagnose malicious input manipulations such...
Pavel Chizhov, Egor Bogomolov, Ivan P. Yamshchikov
Efficiency and safety of Large Language Models (LLMs), among other factors, rely on the quality of tokenization. A good tokenizer not only improves...
Djiré Albérick Euraste, Kaboré Abdoul Kader, Jordan Samhi +3 more
The lack of transparency about code datasets used to train large language models (LLMs) makes it difficult to detect, evaluate, and mitigate data...
Yi Ting Shen, Kentaroh Toyoda, Alex Leung
The rapid proliferation of Model Context Protocol (MCP)-based agentic systems has introduced a new category of security threats that existing...
Xixun Lin, Yang Liu, Yancheng Chen +9 more
The performance of large language model (LLM) agents depends critically on the execution harness, the system layer that orchestrates tool use,...
Xiaohua Wang, Muzhao Tian, Yuqi Zeng +20 more
Reinforcement Learning from Human Feedback (RLHF) and related alignment paradigms have become central to steering large language models (LLMs) and...
Sujan Ghimire, Parsa Mirfasihi, Muhtasim Alam Chowdhury +6 more
The globalization of integrated circuit (IC) design and manufacturing has increased the exposure of hardware intellectual property (IP) to untrusted...
Prajas Wadekar, Venkata Sai Pranav Bachina, Kunal Bhosikar +2 more
3D Gaussian Splatting (3DGS) has recently enabled highly photorealistic 3D reconstruction from casually captured multi-view images. However, this...
Joel Fokou
Autonomous AI agents are rapidly transitioning from experimental tools to operational infrastructure, with projections that 80% of enterprise...
Shaopeng Fu, Di Wang
Adversarial training (AT) is an effective defense for large language models (LLMs) against jailbreak attacks, but performing AT on LLMs is costly. To...
Anasuya Chattopadhyay, Daniel Reti, Hans D. Schotten
Cloud networks increasingly rely on machine learning based Network Intrusion Detection Systems to defend against evolving cyber threats. However,...
Vladimir A. Mazin, Mikhail A. Zorin, Dmitrii S. Korzh +3 more
Passwords still remain a dominant authentication method, yet their security is routinely subverted by predictable user choices and large-scale...
Miit Daga, Swarna Priya Ramu
Organisations increasingly outsource privacy-sensitive data transformations to cloud providers, yet no practical mechanism lets the data owner verify...
Rui Yin, Tianxu Han, Naen Xu +8 more
Safety-aligned large language models (LLMs) are increasingly deployed in real-world pipelines, yet this deployment also enlarges the supply-chain...
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