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20172026
most citedThreats, Protection and Attribution of Cyber Attacks on Critical Infrastructures

11 citations · 20 across the 19 of their papers we have counts for

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cs.CR2026

-SecBench: A Large-Scale Evaluation Suite of Security, Resilience, and Trust for LLM-based UAV Agents over 6G Networks

Mohamed Amine Ferrag, Abderrahmane Lakas, Merouane Debbah

Autonomous unmanned aerial vehicle (UAV) systems are increasingly deployed in safety-critical, networked environments where they must operate reliably in the presence of malicious…

cs.CR2025

The Hidden DNA of LLM-Generated JavaScript: Structural Patterns Enable High-Accuracy Authorship Attribution

Norbert Tihanyi, Bilel Cherif, Richard A. Dubniczky +2

In this paper, we present the first large-scale study exploring whether JavaScript code generated by Large Language Models (LLMs) can reveal which model produced it, enabling relia…

cs.CR2025

Reliability and Resilience of AI-Driven Critical Network Infrastructure under Cyber-Physical Threats

Konstantinos A. Lizos, Leandros Maglaras, Elena Petrovik +3

The increasing reliance on AI-driven 5G/6G network infrastructures for mission-critical services highlights the need for reliability and resilience against sophisticated cyber-phys…

cs.CR2025

Innovating Augmented Reality Security: Recent E2E Encryption Approaches

Hamish Alsop, Leandros Maglaras, Helge Janicke +2

End-to-end encryption (E2EE) has emerged as a fundamental element of modern digital communication, protecting data from unauthorized access during transmission. By design, E2EE ens…

cs.CR2025

From Prompt Injections to Protocol Exploits: Threats in LLM-Powered AI Agents Workflows

Mohamed Amine Ferrag, Norbert Tihanyi, Djallel Hamouda +3

Autonomous AI agents powered by large language models (LLMs) with structured function-calling interfaces enable real-time data retrieval, computation, and multi-step orchestration.…

cs.CR2025

CASTLE: Benchmarking Dataset for Static Code Analyzers and LLMs towards CWE Detection

Richard A. Dubniczky, Krisztofer Zoltán Horvát, Tamás Bisztray +3

Identifying vulnerabilities in source code is crucial, especially in critical software components. Existing methods such as static analysis, dynamic analysis, formal verification,…