@article{RojekIslamHartmannetal.2021, author = {Rojek, Lukasz and Islam, Saiful and Hartmann, Michael and Creutzburg, Reiner}, title = {IoT-Based Real-Time Monitoring System for a Smart Energy House}, series = {Electronic Imaging}, journal = {Electronic Imaging}, publisher = {Society for Imaging Science and Technology}, address = {Springfield, VA}, issn = {2470-1173}, doi = {10.2352/ISSN.2470-1173.2021.3.MOBMU-038}, pages = {38-1 -- 38-10}, year = {2021}, language = {en} } @article{WhiskerdKoertgeJuergensetal.2020, author = {Whiskerd, Nicholas and K{\"o}rtge, Nicklas and J{\"u}rgens, Kris and Ezennaya-Gomez, Salatiel and Vielhauer, Claus and Dittmann, Jana and Hildebrandt, Mario}, title = {Keystroke biometrics in the encrypted domain: a first study on search suggestion functions of web search engines}, series = {EURASIP Journal on Information Security}, journal = {EURASIP Journal on Information Security}, number = {2020:2}, publisher = {Springer}, doi = {10.1186/s13635-020-0100-8}, year = {2020}, language = {en} } @article{LamshoeftNeubertHielscheretal.2022, author = {Lamsh{\"o}ft, Kevin and Neubert, Tom and Hielscher, Jonas and Vielhauer, Claus}, title = {Knock, knock, log: Threat analysis, detection \& mitigation of covert channels in syslog using port scans as cover}, series = {Forensic Science International: Digital Investigation}, volume = {40}, journal = {Forensic Science International: Digital Investigation}, publisher = {Elsevier}, issn = {2666-2817}, doi = {10.1016/j.fsidi.2022.301335}, year = {2022}, language = {en} } @article{SteinPilgermannWeberetal.2025, author = {Stein, Stefan and Pilgermann, Michael and Weber, Simon and Sedlmayr, Martin}, title = {Leveraging MDS2 and SBOM data for LLM-assisted vulnerability analysis of medical devices}, series = {Computational and Structural Biotechnology Journal}, volume = {28}, journal = {Computational and Structural Biotechnology Journal}, publisher = {Elsevier}, doi = {10.1016/j.csbj.2025.07.012}, pages = {267 -- 280}, year = {2025}, abstract = {This study investigated the use of a semi-automated, Retrieval-Augmented Generation (RAG)-based multi-agent architecture to analyze security-relevant data and assemble specialized exploitation paths targeting medical devices. The input dataset comprised device-specific sources, namely, the Manufacturer Disclosure Statement for Medical Device Security (MDS2) documents and Software Bills of Materials (SBOMs), enriched with public vulnerability databases, including Common Vulnerabilities and Exposures (CVE), Known Exploited Vulnerabilities (KEV), and Metasploit exploit records. The objective was to assess whether a modular, Large Language Model (LLM)-driven agent system could autonomously correlate device metadata with known vulnerabilities and existing exploit information to support structured threat modeling. The architecture follows a static RAG design based on predefined prompts and fixed retrieval logic, without autonomous agent planning or dynamic query adaptation. The developed Vulnerability Intelligence for Threat Analysis in Medical Security (VITAMedSec) system operates under human-prompted supervision and successfully synthesizes actionable insights and exploitation paths without requiring manual step-by-step input during execution. Although technically coherent results were obtained under controlled conditions, real-world validation remains a critical avenue for future research. This study further discusses the dual-use implications of such an agent-based framework, its relevance to patient safety in medical device cybersecurity, and the broader applicability of the proposed architecture to other critical infrastructure sectors. These findings emphasize both the technical potential and ethical responsibility for applying semi-automated AI workflows in medical cybersecurity contexts.}, language = {en} } @inproceedings{LepperOehlerKinzleretal.2023, author = {Lepper, Markus and Oehler, Michael and Kinzler, Hartmuth and Tranc{\´o}n y Widemann, Baltasar}, title = {Mathematische Remodellierung zur Erforschung der exakten Semantik einfacher konventioneller Notationssysteme}, series = {Notation. Schnittstelle zwischen Komposition, Interpretation und Analyse. 19. Jahreskongress der Gesellschaft f{\"u}r Musiktheorie Z{\"u}rich 2019 (GMTH Proceedings 2019)}, booktitle = {Notation. Schnittstelle zwischen Komposition, Interpretation und Analyse. 19. Jahreskongress der Gesellschaft f{\"u}r Musiktheorie Z{\"u}rich 2019 (GMTH Proceedings 2019)}, publisher = {Gesellschaft f{\"u}r Musiktheorie (GMTH) e.V.}, doi = {10.31751/p.257}, pages = {69 -- 85}, year = {2023}, abstract = {Das Projekt semPart - Semantik der Partitur versucht, durch {\"U}bertragung von Methoden der Informatik auf die musikalische Notation exakte Aussagen {\"u}ber deren Semantik zu erzielen. Dies geschieht durch Remodellierung, also durch das Erstellen kleiner mathematischer Modelle, die jeweils das historisch-kulturell bestimmte Dekodieren von isolierten Parameter-Schichten eines Notates nachbilden. Erstes wichtiges Ergebnis ist, dass es in keinem Bereich jemals eine einzige ›richtige‹ Definition von Syntax und Semantik geben kann, sondern einen Katalog von vielf{\"a}ltigen theoretisch m{\"o}glichen und in der Praxis auch angetroffenen Varianten. Diese sind durch ihre Remodellierung exakt identifizier- und benennbar; ihre Gesamtheit bildet ein Raster, durch das Notationsstile und -werkzeuge beschreib- und vergleichbar werden. Dieses Raster und die Remodelle sind besonders politisch wichtig, zur F{\"o}rderung einer {\"o}ffentlichen Diskussion von Notationssystemen und ihren Eigenschaften, da zunehmend die Arbeitsweise von digitalen Werkzeugen die notationelle Praxis zu {\"u}berformen und zu filtrieren droht. The project semPart - Semantics of the Musical Score tries to clarify the semantics of musical notation by applying methods from informatics. This is done by remodelling, i. e., constructing small mathematical models that mimic the mentally and culturally determined processes taking place when decoding isolated parameters in musical notation. The first important result is that there can never be one single 'correct' definition of semantics in any area but rather a catalogue of many theoretically possible variants encountered in practice. Through their remodelling, these can be precisely identified and named; their totality constitutes a classification grid applicable to styles, corpora, single scores and digital tools such as editors or encoding standards. This grid and the remodels are of particular political importance in promoting a public discussion on notation systems and their characteristics, given that the increasing use of digital processing systems threatens to over-shape and narrow down notational practice.}, language = {de} } @article{JohannsenKantCreutzburg2020, author = {Johannsen, Andreas and Kant, Daniel and Creutzburg, Reiner}, title = {Measuring IT security, compliance and data governance within small and medium-sized IT enterprises}, series = {IS and T International Symposium on Electronic Imaging Science and Technology}, journal = {IS and T International Symposium on Electronic Imaging Science and Technology}, publisher = {Society for Imaging Science and Technology (IS\&T)}, address = {Springfield, VA}, issn = {2470-1173}, doi = {10.2352/ISSN.2470-1173.2020.3.MOBMU-252}, pages = {252-1 -- 252-11}, year = {2020}, language = {en} } @inproceedings{WagnerKitzelmannBoersch2025, author = {Wagner, Robin and Kitzelmann, Emanuel and Boersch, Ingo}, title = {Mitigating Hallucination by Integrating Knowledge Graphs into LLM Inference - a Systematic Literature Review}, series = {Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop)}, booktitle = {Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop)}, publisher = {Association for Computational Linguistics}, address = {Vienna}, doi = {10.18653/v1/2025.acl-srw.53}, pages = {795 -- 805}, year = {2025}, abstract = {Large Language Models (LLMs) demonstrate strong performance on different language tasks, but tend to hallucinate - generate plausible but factually incorrect outputs. Recently, several approaches to integrate Knowledge Graphs (KGs) into LLM inference were published to reduce hallucinations. This paper presents a systematic literature review (SLR) of such approaches. Following established SLR methodology, we identified relevant work by systematically search in different academic online libraries and applying a selection process. Nine publications were chosen for indepth analysis. Our synthesis reveals differences and similarities of how the KG is accessed, traversed, and how the context is finally assembled. KG integration can significantly improve LLM performance on benchmark datasets and additionally to mitigate hallucination enhance reasoning capabilities, explainability, and access to domain-specific knowledge. We also point out current limitations and outline directions for future work.}, language = {en} } @article{SchwarzSchwarzCreutzburg2020, author = {Schwarz, Franziska and Schwarz, Klaus and Creutzburg, Reiner}, title = {New Methodology and Checklist of Wi-Fi Connected and App-Controlled IoT-Based Consumer Market Smart Home Devices}, series = {Electronic Imaging}, journal = {Electronic Imaging}, publisher = {Society for Imaging Science and Technology}, address = {Springfield, VA}, issn = {2470-1173}, doi = {10.2352/ISSN.2470-1173.2020.3.MOBMU-276}, pages = {276-1 -- 276-15}, year = {2020}, language = {en} } @article{JohnWeizelHeumannetal.2021, author = {John, Stefanie and Weizel, David and Heumann, Anna Sophie and Fischer, Anja and Orlowski, Katja and Mrkor, Kai-Uwe and Edelmann-Nusser, J{\"u}rgen and Witte, Kerstin}, title = {Persisting inter-limb differences in patients following total hip arthroplasty four to five years after surgery? A preliminary cross-sectional study}, series = {BMC Musculoskelet Disorders}, volume = {22}, journal = {BMC Musculoskelet Disorders}, publisher = {BioMed Central}, issn = {1471-2474}, doi = {10.1186/s12891-021-04099-7}, year = {2021}, language = {en} } @article{BeckSchraderTetzlaffetal.2018, author = {Beck, Eberhard and Schrader, Thomas and Tetzlaff, Laura and Schr{\"o}der, Cornelia}, title = {Prospektive Risikoanalyse: Die {\"A}hnlichkeit von Medikamentennamen in der Drugbank-Datenbank}, series = {GMS Medizinische Informatik, Biometrie und Epidemiologie}, volume = {14}, journal = {GMS Medizinische Informatik, Biometrie und Epidemiologie}, number = {2}, doi = {10.3205/mibe000187}, pages = {1/7 -- 7/7}, year = {2018}, language = {de} }