2,077+ academic papers on AI security, attacks, and defenses
Showing 321–340 of 343 papers
Clear filtersSarthak Munshi, Manish Bhatt, Vineeth Sai Narajala +4 more
While prior work has focused on projecting adversarial examples back onto the manifold of natural data to restore safety, we argue that a...
Kimberly T. Mai, Anna Gausen, Magda Dubois +5 more
AI is increasingly being used to assist fraud and cybercrime. However, it is unclear the extent to which current large language models can provide...
Zheng Gao, Xiaoyu Li, Zhicheng Bao +2 more
Generative images have proliferated on Web platforms in social media and online copyright distribution scenarios, and semantic watermarking has...
Yongchang Zhang, Oliver Ma, Tianyi Liu +2 more
Recent large vision-language models (LVLMs) have demonstrated impressive reasoning ability by generating long chain-of-thought (CoT) responses....
Inderjeet Singh, Vikas Pahuja, Aishvariya Priya Rathina Sabapathy +8 more
Current stateless defences for multimodal agentic RAG fail to detect adversarial strategies that distribute malicious semantics across retrieval,...
Yonathan Arbel, Peter Salib, Simon Goldstein
Very soon, millions of AI agents will proliferate across the economy, autonomously taking billions of actions. Inevitably, things will go wrong....
Nazanin Mohammadi Sepahvand, Eleni Triantafillou, Hugo Larochelle +3 more
Large language models (LLMs) trained on webscale data can produce toxic outputs, raising concerns for safe deployment. Prior defenses, based on...
Xuan Chen, Hao Liu, Tao Yuan +3 more
Traditional phishing website detection relies on static heuristics or reference lists, which lag behind rapidly evolving attacks. While recent...
Mengxuan Hu, Vivek V. Datla, Anoop Kumar +4 more
Recent advances in alignment techniques such as Supervised Fine-Tuning (SFT), Reinforcement Learning from Human Feedback (RLHF), and Direct...
Morteza Eskandarian, Mahdi Rabbani, Arun Kaniyamattam +6 more
The current generation of large language models produces sophisticated social-engineering content that bypasses standard text screening systems in...
Xinfeng Li, Shenyu Dai, Kelong Zheng +4 more
Large language model (LLM) agents are rapidly becoming trusted copilots in high-stakes domains like software development and healthcare. However,...
Mohammed Cherifi
Public EV charging infrastructure suffers from significant failure rates -- with field studies reporting up to 27.5% of DC fast chargers...
Guangnian Wan, Qi Li, Gongfan Fang +2 more
Multimodal Diffusion Language Models (MDLMs) have recently emerged as a competitive alternative to their autoregressive counterparts. Yet their...
Yanna Jiang, Delong Li, Haiyu Deng +4 more
Agentic systems increasingly rely on reusable procedural capabilities, \textit{a.k.a., agentic skills}, to execute long-horizon workflows reliably....
Piyush Jaiswal, Aaditya Pratap, Shreyansh Saraswati +2 more
Large Language Models (LLMs) are widely deployed in real-world systems. Given their broader applicability, prompt engineering has become an efficient...
Shruti Srivastava, Kiranmayee Janardhan, Shaurya Jauhari
Cybersecurity threats are becoming increasingly sophisticated, making traditional defense mechanisms and manual red teaming approaches insufficient...
Che Wang, Jiaming Zhang, Ziqi Zhang +6 more
The integration of external data services (e.g., Model Context Protocol, MCP) has made large language model-based agents increasingly powerful for...
Che Wang, Fuyao Zhang, Jiaming Zhang +6 more
Large Language Model (LLM) agents are susceptible to Indirect Prompt Injection (IPI) attacks, where malicious instructions in retrieved content...
Longxiang Wang, Xiang Zheng, Xuhao Zhang +3 more
Multi-tenant LLM serving frameworks widely adopt shared Key-Value caches to enhance efficiency. However, this creates side-channel vulnerabilities...
Yige Liu, Yiwei Lou, Che Wang +2 more
As a distributed collaborative machine learning paradigm, vertical federated learning (VFL) allows multiple passive parties with distinct features...
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