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Auflistung nach Autor:in "Matzutt, Roman"

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  • Textdokument
    myneData: Towards a Trusted and User-controlled Ecosystem for Sharing Personal Data
    (INFORMATIK 2017, 2017) Matzutt, Roman; Müllmann, Dirk; Zeissig, Eva-Maria; Horst, Christiane; Kasugai, Kai; Lidynia, Sean; Wieninger, Simon; Ziegeldorf, Jan Henrik; Gudergan, Gerhard; gen. Döhmann, Indra Spiecker; Wehrle, Klaus; Ziefle, Martina
    Personal user data is collected and processed at large scale by a handful of big providers of Internet services. This is detrimental to users, who often do not understand the privacy implications of this data collection, as well as to small parties interested in gaining insights from this data pool, e.g., research groups or small and middle-sized enterprises. To remedy this situation, we propose a transparent and user-controlled data market in which users can directly and consensually share their personal data with interested parties for monetary compensation. We define a simple model for such an ecosystem and identify pressing challenges arising within this model with respect to the user and data processor demands, legal obligations, and technological limits. We propose myneData as a conceptual architecture for a trusted online platform to overcome these challenges. Our work provides an initial investigation of the resulting myneData ecosystem as a foundation to subsequently realize our envisioned data market via the myneData platform.
  • Konferenzbeitrag
    On Data Spaces for Retrieval Augmented Generation
    (INFORMATIK 2024, 2024) Hermsen, Felix; Nitz, Lasse; Akbari Gurabi, Mehdi; Matzutt, Roman; Mandal, Avikarsha
    Large Language Models (LLMs) have revolutionized knowledge retrieval from natural language queries. However, LLMs still face challenges regarding the creation of domain-specific and accurate answers. Recently, Retrieval Augmented Generation (RAG) architecture has been proposed as one approach to addressing these challenges. While current research focuses on optimizing document retrieval and augmenting the initial query accordingly, we identify untapped potentials of RAG to retrieve knowledge from heterogeneous data sources via data spaces. In this work, we investigate three conceptual integration scenarios between RAG and data spaces. Our findings indicate that given the data space extended RAG, it could provide domain-specific information retrieval with diverse data sources. However, solutions to mitigate unintended information leakage require further consideration.
  • Textdokument
    Putting Privacy into Perspective – Comparing Technical, Legal, and Users’ View of Information Sensitivity
    (INFORMATIK 2020, 2021) Schomakers, Eva-Maria; Lidynia, Chantal; Müllmann, Dirk; Matzutt, Roman; Wehrle, Klaus; Spiecker genannt Döhmann, Indra; Ziefle, Martina
    Social media, cloud computing, and the Internet of Things connect people around the globe, offering manifold benefits. However, the technological advances and increased user participation generate novel challenges for users' privacy. From the users' perspective, the consequences of data disclosure depend on the perceived sensitivity of that data. But in light of the new technological opportunities to process and combine data, it is questionable whether users can adequately evaluate risks of data disclosures. As mediating authority, data protection laws such as the European General Data Protection Regulation try to protect user data, granting enhanced protection to “special categories” of data. In this paper, we assess the legal, technological, and users' perspectives on information sensitivity and their interplay. Technologically, all data can be referred to as “potentially sensitive.” The legal and users' perspective on information sensitivity deviate from this standpoint, as some data types are granted special protection by law but are not perceived as very sensitive by users and vice versa. Our key findings still suggest the GDPR adequately protecting users' privacy but for small adjustments.