2,589+ academic papers on AI security, attacks, and defenses
Showing 1661–1680 of 2,589 papers
Md. Hasib Ur Rahman
As Large Language Models (LLMs) become ubiquitous, the challenge of securing them against adversarial "jailbreaking" attacks has intensified. Current...
Sanjay Das, Swastik Bhattacharya, Shamik Kundu +3 more
State-space models (SSMs), exemplified by the Mamba architecture, have recently emerged as state-of-the-art sequence-modeling frameworks, offering...
Luoxi Meng, Henry Feng, Ilia Shumailov +1 more
Browser-using agents (BUAs) are an emerging class of AI agents that interact with web browsers in human-like ways, including clicking, scrolling,...
Yixin Tan, Zhe Yu, Jun Sakuma
Finetuning pretrained large language models (LLMs) has become the standard paradigm for developing downstream applications. However, its security...
Safwan Shaheer, G. M. Refatul Islam, Mohammad Rafid Hamid +3 more
Prompt injection attacks can compromise the security and stability of critical systems, from infrastructure to large web applications. This work...
Arastoo Zibaeirad, Marco Vieira
Large Language Models (LLMs) are increasingly being studied for Software Vulnerability Detection (SVD) and Repair (SVR). Individual LLMs have...
J. Alexander Curtis, Nasir U. Eisty
Penetration testing is a cornerstone of cybersecurity, traditionally driven by manual, time-intensive processes. As systems grow in complexity, there...
Dang-Khoa Nguyen, Gia-Thang Ho, Quang-Minh Pham +5 more
Software supply chain attacks targeting the npm ecosystem have become increasingly sophisticated, leveraging obfuscation and complex logic to evade...
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...
Padmeswari Nandiya, Ahmad Mohsin, Ahmed Ibrahim +2 more
Industry 5.0's increasing integration of IT and OT systems is transforming industrial operations but also expanding the cyber-physical attack...
Xin Yang, Omid Ardakanian
Data obfuscation is a promising technique for mitigating attribute inference attacks by semi-trusted parties with access to time-series data emitted...
Peichun Hua, Hao Li, Shanghao Shi +2 more
Large Vision-Language Models (LVLMs) are vulnerable to a growing array of multimodal jailbreak attacks, necessitating defenses that are both...
Jie Ma, Junqing Zhang, Guanxiong Shen +2 more
Radio frequency fingerprint identification (RFFI) is an emerging technique for the lightweight authentication of wireless Internet of things (IoT)...
Edward Lue Chee Lip, Anthony Channg, Diana Kim +2 more
As AI capabilities advance, we increasingly rely on powerful models to decompose complex tasks $\unicode{x2013}$ but what if the decomposer itself is...
Andrew Adiletta, Kathryn Adiletta, Kemal Derya +1 more
The rapid deployment of Large Language Models (LLMs) has created an urgent need for enhanced security and privacy measures in Machine Learning (ML)....
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...
Jing Cui, Yufei Han, Jianbin Jiao +1 more
Backdoor attacks embed malicious behaviors into Large Language Models (LLMs), enabling adversaries to trigger harmful outputs or bypass safety...
Alexander K. Saeri, Sophia Lloyd George, Jess Graham +4 more
Organizations and governments that develop, deploy, use, and govern AI must coordinate on effective risk mitigation. However, the landscape of AI...
Manon Kempermann, Sai Suresh Macharla Vasu, Mahalakshmi Raveenthiran +2 more
Safety evaluations of large language models (LLMs) typically focus on universal risks like dangerous capabilities or undesirable propensities....
Neha, Tarunpreet Bhatia
Intrusion Detection Systems (IDS) are critical components in safeguarding 5G/6G networks from both internal and external cyber threats. While...
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