2,077+ academic papers on AI security, attacks, and defenses
Showing 1761–1780 of 2,037 papers
Clear filtersKarthik Avinash, Nikhil Pareek, Rishav Hada
The increasing deployment of Large Language Models (LLMs) across enterprise and mission-critical domains has underscored the urgent need for robust...
Yuan Feng, Haoyu Guo, JunLin Lv +2 more
Large language models have revolutionized natural language processing, yet their deployment remains hampered by the substantial memory and runtime...
Baogang Song, Dongdong Zhao, Jianwen Xiang +2 more
Backdoor attacks pose a persistent security risk to deep neural networks (DNNs) due to their stealth and durability. While recent research has...
Jiarui Li, Yuhan Chai, Lei Du +3 more
Rule-based network intrusion detection systems play a crucial role in the real-time detection of Web attacks. However, most existing works primarily...
Juan Ren, Mark Dras, Usman Naseem
Large Vision-Language Models (LVLMs) unlock powerful multimodal reasoning but also expand the attack surface, particularly through adversarial inputs...
Ruoyu Sun, Da Song, Jiayang Song +2 more
As Large Language Models (LLMs) continue to revolutionize Natural Language Processing (NLP) applications, critical concerns about their...
João A. Leite, Arnav Arora, Silvia Gargova +5 more
Large Language Models (LLMs) can generate human-like disinformation, yet their ability to personalise such content across languages and demographics...
Tuan T. Nguyen, John Le, Thai T. Vu +2 more
Large language models (LLMs) achieve impressive performance across diverse tasks yet remain vulnerable to jailbreak attacks that bypass safety...
Ruben Belo, Marta Guimaraes, Claudia Soares
Large Language Models are susceptible to jailbreak attacks that bypass built-in safety guardrails (e.g., by tricking the model with adversarial...
Siyuan Li, Aodu Wulianghai, Xi Lin +4 more
With the increasing integration of large language models (LLMs) into open-domain writing, detecting machine-generated text has become a critical task...
Masoud Makrehchi
Artificial Intelligence (AI) has emerged as both a continuation of historical technological revolutions and a potential rupture with them. This paper...
Francesco Giarrusso, Olga E. Sorokoletova, Vincenzo Suriani +1 more
Jailbreaking techniques pose a significant threat to the safety of Large Language Models (LLMs). Existing defenses typically focus on single-turn...
Daniel Pulido-Cortázar, Daniel Gibert, Felip Manyà
Over the last decade, machine learning has been extensively applied to identify malicious Android applications. However, such approaches remain...
Sifan Li, Hongkai Chen, Yujun Cai +4 more
Vision Language Models (VLMs) have achieved impressive progress in multimodal reasoning; yet, they remain vulnerable to hallucinations, where outputs...
Ozan K. Tonguz, Federico Taschin
One of the major problems in Machine Learning (ML) and Artificial Intelligence (AI) is the fact that the probability distribution of the test data in...
Blazej Manczak, Eric Lin, Francisco Eiras +2 more
Large language models (LLMs) are rapidly transitioning into medical clinical use, yet their reliability under realistic, multi-turn interactions...
Yuqi Jia, Yupei Liu, Zedian Shao +2 more
Prompt injection attacks deceive a large language model into completing an attacker-specified task instead of its intended task by contaminating its...
Dongsen Zhang, Zekun Li, Xu Luo +3 more
The Model Context Protocol (MCP) standardizes how large language model (LLM) agents discover, describe, and call external tools. While MCP unlocks...
Bowen Fan, Zhilin Guo, Xunkai Li +5 more
Graph Neural Networks (GNNs) have become a pivotal framework for modeling graph-structured data, enabling a wide range of applications from social...
Xiaoxue Ren, Penghao Jiang, Kaixin Li +6 more
Web applications are prime targets for cyberattacks as gateways to critical services and sensitive data. Traditional penetration testing is costly...
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