An Approach for a Supporting Multi-LLM System for Automated Certification Based on the German IT-Grundschutz

Computer Science > Cryptography and Security [Submitted on 24 Jun 2026] An Approach for a Supporting Multi-LLM System for Automated Certification Based on the German IT-Grundschutz Lea Roxanne Muth, Marian Margraf This paper presents a novel approach to perform semi-automated BSI IT-Grundschutz certification using a MultiLarge Language Model system (MLS) with Hybrid RetrievalAugmented Generation (HybridRAG). Facing the challenges of the Network and Information Security Directive 2 (NIS2) directive, a shortage of specialists, and high implementation costs, our MLS architecture aims to increase efficiency, reduce costs, and support certifiers in maintaining the quality of security concepts while meeting the increased demand for certifications of newly affected companies. The system combines Large Language Models (LLMs) and Knowledge Graphs (KGs) to support different phases of the certification process, including protection needs assessment, modeling, IT-Grundschutz check, measure consolidation, and subsequent realization. Our architecture addresses the growing demand for security concepts and offers an approach to handle the digital security challenges introduced by NIS2. Comments: Accepted for publication at the 2025 IEEE International Conference on Cyber Security and Resilience (IEEE CSR), Chania, Crete, Greece, August 4-6, 2025. 8 pages, 2 figures Subjects: Cryptography and Security (cs.CR); Artificial Intelligence (cs.AI) Cite as: arXiv:2606.25608 [cs.CR]   (or arXiv:2606.25608v1 [cs.CR] for this version)   https://doi.org/10.48550/arXiv.2606.25608 Focus to learn more Related DOI: https://doi.org/10.1109/CSR64739.2025.11130171 Focus to learn more Submission history From: Lea R. Muth [view email] [v1] Wed, 24 Jun 2026 09:16:13 UTC (843 KB) Access Paper: HTML (experimental) view license Current browse context: cs.CR < prev   |   next > new | recent | 2026-06 Change to browse by: cs cs.AI References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)