@article{SchwarzSchwarzFuchsetal.2021, author = {Schwarz, Franziska and Schwarz, Klaus and Fuchs, Daniel and Creutzburg, Reiner and Akopian, David}, title = {Firmware Vulnerability Analysis of Widely Used Low-Budget TP-Link Routers}, 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-135}, pages = {135-1 -- 135-11}, year = {2021}, language = {en} } @article{SchwarzCreutzburg2021, author = {Schwarz, Klaus and Creutzburg, Reiner}, title = {Design of Professional Laboratory Exercises for Effective State-of-the-Art OSINT Investigation Tools - Part 1: RiskIQ Passive-Total}, 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-043}, pages = {43-1 -- 43-7}, year = {2021}, language = {en} } @article{SchwarzCreutzburg2021, author = {Schwarz, Klaus and Creutzburg, Reiner}, title = {Design of Professional Laboratory Exercises for Effective State-of-the-Art OSINT Investigation Tools - Part 2: Censys}, 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-044}, pages = {44-1 -- 44-8}, year = {2021}, language = {en} } @article{SchwarzCreutzburg2021, author = {Schwarz, Klaus and Creutzburg, Reiner}, title = {Design of Professional Laboratory Exercises for Effective State-of-the-Art OSINT Investigation Tools - Part 3: Maltego}, series = {Electronic Imaging}, journal = {Electronic Imaging}, publisher = {Society for Imaging Science and Technology}, address = {Springfield, VA}, doi = {10.2352/ISSN.2470-1173.2021.3.MOBMU-045}, pages = {45-1 -- 45-23}, year = {2021}, language = {en} } @article{SchwarzSchwarzCreutzburg2020, author = {Schwarz, Klaus and Schwarz, Franziska and Creutzburg, Reiner}, title = {Conception and implementation of professional laboratory exercises in the field of open source intelligence (OSINT)}, 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-278}, pages = {278-1 -- 278-10}, year = {2020}, language = {en} } @article{SteinPilgermannSedlmayr2025, author = {Stein, Stefan and Pilgermann, Michael and Sedlmayr, Martin}, title = {Systematic Evaluation of Manufacturer Disclosure Statements for Medical Device Security (MDS2) to Strengthen Hospital OT Security Measures - Lessons Learned}, series = {Studies in health technology and informatics}, volume = {331}, journal = {Studies in health technology and informatics}, doi = {10.3233/SHTI251404}, pages = {256 -- 264}, year = {2025}, abstract = {The growing number of connected medical devices in hospitals poses serious operational technology (OT) security challenges. Effective countermeasures require a structured analysis of the communication interfaces and security configurations of individual devices. State of the art: Although Manufacturer Disclosure Statements for Medical Device Security (MDS2, Version 2019) offer relevant information, they are rarely integrated into cybersecurity workflows. Existing studies are limited in scope and lack scalable methodologies for systematic evaluation. Concept: This study analyzed 209 MDS2 documents and 161 security white papers to extract structured information on ports, protocols, and protective measures. Over 52,000 question-answer pairs were converted into a machine-readable format using customized parsing and validation routines. The aim was to establish whether this dataset could inform risk assessments and future applications involving Large Language Models (LLMs). Implementation: The analysis revealed 367 distinct ports, including common protocols such as HTTPS (443), DICOM (104), and RDP (3389), as well as vendor-specific proprietary ports. Approximately 40\% of the devices used over 20 ports, indicating a broad attack surface. OCR errors and inconsistent formatting required manual corrections. A consolidated dataset was developed to support clustering, comparison across vendors and versions, and preparation for downstream LLM use, particularly via structured SBOM and configuration data. Lessons learned: Although no model training was conducted, the structured dataset can support AI-based OT security workflows. The findings highlight the critical need for up-to-date, machine-readable manufacturer data in standardized formats and schemas. Such information could greatly enhance the automation, comparability, and scalability of hospital cybersecurity measures.}, 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} } @article{VaherTammSalusetal.2023, author = {Vaher, Ivi and Tamm, Anna-Liisa and Salus, Marit and Reisberg, Kirkke and V{\"a}hi, Aleksandra and Pallon, Helena and Paeste, Andra and Pirk, B{\"a}thel-Betty and Merila, Margus and Schrader, Thomas}, title = {Effectiveness of massage chair and classic massage in recovery from physical exertion: a pilot study}, series = {Journal of Novel Physiotherapy and Rehabilitation}, volume = {2023}, journal = {Journal of Novel Physiotherapy and Rehabilitation}, number = {7}, publisher = {HSPI}, doi = {10.29328/journal.jnpr.1001050}, pages = {8 -- 15}, year = {2023}, abstract = {Quick and cost-effective recovery is foundational to high-quality training and good competition results in today's sports. The aim of the research was to elucidate the effects of hand and massage chair massage on the biomechanical parameters of muscles of lower limbs and back, indicators of Pain Pressure Thresholds (PPT) and subjectively perceived fatigue. A total of 32 female recreational athletes (18 - 50 years old) were assigned to a hand massage, massage chair, or lying down the group. They were measured for muscle biomechanical properties (MyotonPro), PPT (Wagner Instruments) and subjectively perceived fatigue (VAS scale) before and after fatigue tests and treatment. The recovery procedure and subjective satisfaction with treatment were rated on a Likert scale. Changes in the median value of m. rectus femoris and m. gastrocnemius stiffness with treatment showed that hand massage could be more effective in reducing stiffness, as compared to chair massage. Hand massage may have benefits for recovery from physical exertion, but due to the individuality of subjects, detailed methodological studies are needed to evaluate the effects of massage chair vs. hand massage.}, language = {en} } @article{WeberSteinPilgermannetal.2023, author = {Weber, Simon B. and Stein, Stefan and Pilgermann, Michael and Schrader, Thomas}, title = {Attack Detection for Medical Cyber-Physical Systems - A Systematic Literature Review}, series = {IEEE Access}, journal = {IEEE Access}, number = {11}, publisher = {IEEE}, doi = {10.1109/ACCESS.2023.3270225}, pages = {41796 -- 41815}, year = {2023}, abstract = {The threat situation due to cyber attacks in hospitals is emerging and patient life is at risk. One significant source of potential vulnerabilities is medical cyber-physical systems (MCPS). Detecting intrusions in this environment faces challenges different from other domains, mainly due to the heterogeneity of devices, the diversity of connectivity types, and the variety of terminology. To summarize existing results, we conducted a structured literature review (SLR) following the guidelines of Kitchenham et al. for SLRs in software engineering. We developed six research questions regarding detection approach, detection location, included features, adversarial focus, utilized datasets, and intrusion prevention. We identified that most researchers focused on an anomaly-based detection approach at the network layer. The primary focus was on the detection of malicious insiders. While several researchers used publicly available datasets for training and testing their algorithms, the lack of suitable datasets resulted in the development of testbeds consisting of various medical devices. Based on the results, we formulated five future research topics. First, the special conditions of hospital networks, the MCPS deployed within them, and the contrasts to other IT and OT environments should be examined. Thereupon, MCPS-specific datasets should be created that allow researchers to address the health domain's unique requirements and possibilities. At the same time, endeavors aimed at standardization in this area should be supported and expanded. Moreover, the use of medical context for attack detection should be further explored. Last but not least, efforts for MCPS-tailored intrusion prevention should be intensified. This way, the emerging threat landscape can be addressed, IT security in hospitals can be improved, and patient health can be protected.}, 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{YuekselSchwarzCreutzburg2020, author = {Y{\"u}ksel, Benjamin and Schwarz, Klaus and Creutzburg, Reiner}, title = {AI-based anomaly detection for cyberattacks on Windows systems-Creation of a prototype for automated monitoring of the process environment}, 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-331}, pages = {331-1 -- 331-13}, year = {2020}, language = {en} }