1 citations · 2 across the 5 of their papers we have counts for
5 papers
"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…
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…
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…
Optimizing AI-Assisted Code Generation
Simon Torka, Sahin Albayrak
In recent years, the rise of AI-assisted code-generation tools has significantly transformed software development. While code generators have mainly been used to support convention…
ALPACA -- Adaptive Learning Pipeline for Comprehensive AI
Simon Torka, Sahin Albayrak
The advancement of AI technologies has greatly increased the complexity of AI pipelines as they include many stages such as data collection, pre-processing, training, evaluation an…