Natural Visibility Graph (NVG)-based representations provide a promising approach for capturing structural patterns in sequential network traffic. However, whether different cyber-attack classes exhibit distinctive topological signatures in such representations remains insufficiently understood. This study investigates...
A language model agent acts through the tools it is given. The data it reads while working on a task can redirect what it does with those tools. A growing set of techniques for safe and secure agent execution therefore sits between the agent and its tools, aiming to enforce access control, information flow or isolation...
Reshabh K Sharma, Lin-Xi Jiang, Shuo Chen et al.· 0 citations
Web applications are increasingly targeted by cyberattacks that exploit HTTP requests to evade security mechanisms. Traditional web application firewalls (WAFs) rely on rule-based approaches that often exhibit high false positive rates and limited adaptability. Recent studies have explored machine learning techniques a...
A. Riverol, Gustavo Betarte, R. Martínez et al.· 0 citations
As large language model (LLM)-powered agents are increasingly deployed to perform complex, real-world tasks, they face a growing class of attacks that exploit extended user-agent-environment interactions to pursue malicious objectives improbable in single-turn settings. Such long-horizon threats pose significant risks...
Yuhui Wang, Tanqiu Jiang, Jiacheng Liang et al.· 0 citations
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The key findings show that while some detectors can identify attacks that rely on explicit textual instructions or visible image perturbations with moderate to high accuracy, they largely fail against attacks that omit explicit instructions or employ imperceptible perturbations.
Yinuo Liu, Ruohan Xu, Xilong Wang et al.· arXiv.org· 22 citations· ⚡1
With the rise of large language models (LLMs) and concerns about potential misuse, watermarks for generative LLMs have recently attracted much attention. An important aspect of such watermarks is the trade-off between their identifiability and their impact on the quality of the generated text. This paper introduces a s...
Vietnam's Personal Data Protection Law (Law No. 91/2025/QH15) and Decree No. 356/2025/ND-CP, effective January 1, 2026, require organizations to establish and maintain Records of Processing Activities (RoPA). Manual RoPA preparation is labor-intensive, while cloud-hosted large language models (LLMs) may conflict with d...
To Duy Hinh, Anh Le Quoc Nguyen, Tri Van Phan et al.· 0 citations
Precise interference detection and identification are crucial for enhancing the survivability of communication systems in non-cooperative wireless environments. While deep learning (DL) has advanced this field, existing single-task learning (STL) approaches neglect inherent task correlations. Furthermore, emerging mult...
Experimental results demonstrate that ForgetMimic effectively eliminates memory of designated motions while maintaining the normal operation of all other motions, and identifies and resolves two key training mechanisms in robot control that lead to unlearning failure.
Xu-Kun Luan, Zhong-Xiang Lei, Chen Gong et al.· 0 citations
The emergence of multi-class malware attacks such as ransomware, spyware, trojans, etc., presents an increasing and serious threat to cybersecurity, particularly in resourceconstrained environments like IoT devices. Existing machine learning models have achieved nearly perfect accuracy in binary malware classification...
Abdul Khalek Alve, A. Rahman, Saadman Zaman et al.· 0 citations
This work introduces ChronosAttack, a delay-only scheduling attack that changes when authentic tool responses arrive without modifying, adding, removing, or accelerating them, to show that tool-response timing can itself form an attack surface in asynchronous LLM agents.
This work investigates combining Federated Learning with TinyML-based model compression for intrusion detection in IoT environments and preliminary results show that training stability plays a critical role in federated TinyML systems.
Younsoo Park, Seokhyoen Bae, Shasi Kumar Ramachandran Prabhu et al.· 1 citation
