2,077+ academic papers on AI security, attacks, and defenses
Showing 641–660 of 965 papers
Clear filtersAngelo Gaspar Diniz Nogueira, Kayua Oleques Paim, Hendrio Bragança +2 more
The ever-increasing number of Android devices and the accelerated evolution of malware, reaching over 35 million samples by 2024, highlight the...
Yu Cui, Yifei Liu, Hang Fu +4 more
Research on the safety evaluation of large language models (LLMs) has become extensive, driven by jailbreak studies that elicit unsafe responses....
Rong Feng, Suman Saha
Obfuscation poses a persistent challenge for software engineering tasks such as program comprehension, maintenance, testing, and vulnerability...
Andrew Maranhão Ventura D'addario
The integration of Large Language Models (LLMs) into healthcare demands a safety paradigm rooted in \textit{primum non nocere}. However, current...
Junbo Zhang, Ran Chen, Qianli Zhou +2 more
Large language models demonstrate powerful capabilities across various natural language processing tasks, yet they also harbor safety...
Onat Gungor, Roshan Sood, Jiasheng Zhou +1 more
Large Language Models (LLMs) are highly effective for cybersecurity question answering (QA) but are difficult to deploy on edge devices due to their...
Benyamin Tafreshian
Large language models (LLMs) are becoming increasingly integrated into mainstream development platforms and daily technological workflows, typically...
Adarsh Kumarappan, Ayushi Mehrotra
The SmoothLLM defense provides a certification guarantee against jailbreaking attacks, but it relies on a strict "k-unstable" assumption that rarely...
Jiangrui Zheng, Yingming Zhou, Ali Abdullah Ahmad +2 more
Bug bounty platforms (e.g., HackerOne, BugCrowd) leverage crowd-sourced vulnerability discovery to improve continuous coverage, reduce the cost of...
Hong-Hanh Nguyen-Le, Van-Tuan Tran, Dinh-Thuc Nguyen +1 more
The rapid advancement of generators (e.g., StyleGAN, Midjourney, DALL-E) has produced highly realistic synthetic images, posing significant...
Xiaoqing Wang, Keman Huang, Bin Liang +2 more
The rapid advancement of Large Language Model (LLM)-driven multi-agent systems has significantly streamlined software developing tasks, enabling...
Xiangrui Zhang, Zeyu Chen, Haining Wang +1 more
Large Language Models (LLMs) and their agent systems have recently demonstrated strong potential in automating code reasoning and vulnerability...
Qingsong He, Jing Nan, Jiayu Jiao +5 more
Large Language Models can break through knowledge and timeliness limitations by invoking external tools within the Model Context Protocol framework...
Swastik Bhattacharya, Sanjay Das, Anand Menon +3 more
Deep Neural Networks (DNNs) continue to grow in complexity with Large Language Models (LLMs) incorporating vast numbers of parameters. Handling these...
Mohamed Afane, Ying Wang, Juntao Chen
Public health agencies face critical challenges in identifying high-risk neighborhoods for childhood lead exposure with limited resources for...
Saeid Jamshidi, Amin Nikanjam, Negar Shahabi +4 more
As the number of connected IoT devices continues to grow, securing these systems against cyber threats remains a major challenge, especially in...
Itay Hazan, Yael Mathov, Guy Shtar +2 more
Securing AI agents powered by Large Language Models (LLMs) represents one of the most critical challenges in AI security today. Unlike traditional...
Aram Vardanyan
Browser agents enable autonomous web interaction but face critical reliability and security challenges in production. This paper presents findings...
Patrick Amadeus Irawan, Ikhlasul Akmal Hanif, Muhammad Dehan Al Kautsar +3 more
Although the cultural dimension has been one of the key aspects in evaluating Vision-Language Models (VLMs), their ability to remain stable across...
Yinjie Zhao, Heng Zhao, Bihan Wen +1 more
As the development of AI-generated contents (AIGC), multi-modal Large Language Models (LLM) struggle to identify generated visual inputs from real...
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