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cs.CR2025
"Digital Camouflage": The LLVM Challenge in LLM-Based Malware Detection
Ekin Böke, Simon Torka
Large Language Models (LLMs) have emerged as promising tools for malware detection by analyzing code semantics, identifying vulnerabilities, and adapting to evolving threats. Howev…
cs.CR2024★ 1 cited
Exploring AI-Enabled Cybersecurity Frameworks: Deep-Learning Techniques, GPU Support, and Future Enhancements
Tobias Becher, Simon Torka
Traditional rule-based cybersecurity systems have proven highly effective against known malware threats. However, they face challenges in detecting novel threats. To address this i…
cs.CR2024
Android App Feature Extraction: A review of approaches for malware and app similarity detection
Simon Torka, Sahin Albayrak
This paper reviews work published between 2002 and 2022 in the fields of Android malware, clone, and similarity detection. It examines the data sources, tools, and features used in…