2,529+ academic papers on AI security, attacks, and defenses
Showing 181–200 of 312 papers
Clear filtersAhmed M. Hussain, Salahuddin Salahuddin, Panos Papadimitratos
Current Large Language Models (LLMs) safety approaches focus on explicitly harmful content while overlooking a critical vulnerability: the inability...
Yifan Yao, Baojuan Wang, Jinhao Duan +4 more
Chat-based cybercrime has emerged as a pervasive threat, with attackers leveraging real-time messaging platforms to conduct scams that rely on...
Honglin Mu, Jinghao Liu, Kaiyang Wan +4 more
Large Language Models (LLMs) excel at text comprehension and generation, making them ideal for automated tasks like code review and content...
Rahul Yumlembam, Biju Issac, Seibu Mary Jacob +1 more
Since the Internet of Things (IoT) is widely adopted using Android applications, detecting malicious Android apps is essential. In recent years,...
Samruddhi Baviskar
Machine learning models used in financial decision systems operate in nonstationary economic environments, yet adversarial robustness is typically...
A. A. Gde Yogi Pramana, Jason Ray, Anthony Jaya +1 more
Vision--Language Models (VLMs) show significant promise for Medical Visual Question Answering (VQA), yet their deployment in clinical settings is...
Tung-Ling Li, Yuhao Wu, Hongliang Liu
Reward models and LLM-as-a-Judge systems are central to modern post-training pipelines such as RLHF, DPO, and RLAIF, where they provide scalar...
Yidong Chai, Yi Liu, Mohammadreza Ebrahimi +2 more
Social media platforms are plagued by harmful content such as hate speech, misinformation, and extremist rhetoric. Machine learning (ML) models are...
Zhexi Lu, Hongliang Chi, Nathalie Baracaldo +3 more
Membership inference attacks (MIAs) pose a critical privacy threat to fine-tuned large language models (LLMs), especially when models are adapted to...
Seok-Hyun Ga, Chun-Yen Chang
The rapid development of Generative AI is bringing innovative changes to education and assessment. As the prevalence of students utilizing AI for...
Piercosma Bisconti, Marcello Galisai, Matteo Prandi +6 more
Safety mechanisms in LLMs remain vulnerable to attacks that reframe harmful requests through culturally coded structures. We introduce Adversarial...
David Lindner, Charlie Griffin, Tomek Korbak +4 more
Automated control monitors could play an important role in overseeing highly capable AI agents that we do not fully trust. Prior work has explored...
Samruddhi Baviskar
We evaluate adversarial robustness in tabular machine learning models used in financial decision making. Using credit scoring and fraud detection...
Mohammad Mahdi Razmjoo, Mohammad Mahdi Sharifian, Saeed Bagheri Shouraki
Despite their remarkable performance, deep neural networks exhibit a critical vulnerability: small, often imperceptible, adversarial perturbations...
Li Lin, Siyuan Xin, Yang Cao +1 more
Watermarking large language models (LLMs) is vital for preventing their misuse, including the fabrication of fake news, plagiarism, and spam. It is...
Hua Ma, Ruoxi Sun, Minhui Xue +4 more
Accurate time-series forecasting is increasingly critical for planning and operations in low-carbon power systems. Emerging time-series large...
Jamal Al-Karaki, Muhammad Al-Zafar Khan, Rand Derar Mohammad Al Athamneh
The scarcity of cyberattack data hinders the development of robust intrusion detection systems. This paper introduces PHANTOM, a novel adversarial...
Neha, Tarunpreet Bhatia
Intrusion Detection Systems (IDS) are critical components in safeguarding 5G/6G networks from both internal and external cyber threats. While...
Miranda Christ, Noah Golowich, Sam Gunn +2 more
Watermarks are an essential tool for identifying AI-generated content. Recently, Christ and Gunn (CRYPTO '24) introduced pseudorandom...
Botao 'Amber' Hu, Bangdao Chen
The emerging "agentic web" envisions large populations of autonomous agents coordinating, transacting, and delegating across open networks. Yet many...
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