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Cloud Computing


The Cloud Computing paradigm is rapidly transforming the development, deployment, and management of Information Systems on a basic level. Cloud technologies, such as virtualization, application containers, multi-cloud federation and the Intercloud are enabling elasticity, cost-efficiency and scalability for private deployments as well as public offerings. More...

Data Science


Data in today’s business landscape are created and stored at exponentially large scales. Therefore, the need to improve business operations through data-driven decisions has emerged as an important objective for many growing companies. The field of data science addresses those needs by combining computer science, engineering, mathematics, statistics, and predictive modeling to generate analytical insights about data from a variety of sources.  More...

Social Networking


Online Social Networks (OSNs) have become an important part of our everyday online lives. We communicate, share content, and organize meetings and events using OSN platforms. However, even though there is a strong trend towards OSN services to become the main communication medium, most OSN platforms are still proprietary, closed services that keep users from connecting directly and seamlessly to the services of other OSN platforms. More...

Ubiquitous Computing


The Ubiquitous Computing paradigm describes a world in which electronic devices are not only unobtrusively embedded within the human’s environment but also in which electronic devices are interacting with each other to support humans in their daily life. Hence, Ubiquitous Computing deals with a wide range of research topics related to Pervasive Computing, Wearable Computing, Ambient Intelligence, Intelligent Environments, Automotive Computing and Smart Homes. More...

Running Projects



The project DYNAMIC has been chosen as one of the most innovative IT projects in 2016 to be funded with the Software Campus initiative. DYNAMIC deals with distributed online social networks and with the creation of dynamic social graphs based on location, context, and profile data. In current Online Social Networks, relations between users are mostly based on explicitly created connections. In DYNAMIC, we want to extend the concept of explicit connections by implicit, dynamic social graphs. More...



eBiz (Business Information Zone) is an innovation action in the Exploration Area „Digital Finance“ funded by and in cooperation with partners of EIT Digital. The project aims at introducing an innovative financial product, allowing small and medium enterprises to safely, transparently, immediately and cost-efficiently perform financial and administrative tasks, first limited to Hungary, and to be released later in the CEE region. In this context, the project allows to develop and validate both state of the art and novel methods in the area of financial machine learning and graph theory to generate valuable new insights and to classify and predict financial transactions. More...



IC4F - Industrial Communication for Factories is the flagship project with the goal of developing safe, robust, and real- time communication solutions for the manufacturing industry. By mid of 2020, 15 project partners from industry and research will develop a technology toolkit for a trustworthy infrastructure based on industrial information and communications technology (ICT). The project strives for an open architecture that extends across domains and allows a modular extension for new applications and communication technologies. In particular, the technology kit will enable users to select a specific migration path along with the right ICT technologies according to the new requirements in the scope of the industrial Internet / Industry 4.0. The project is supported by the Federal Ministry of Economics and Energy (BMWi) within the PAiCE funding program. More...



The privacy project PARADISE (Privacy-enhancing And Reliable Anti-Doping Integrated Service Environment) is funded by the Federal Ministry of Education and Research (BMBF). The project goal is to increase confidentiality and privacy of athletes' whereabouts data in the context of national anti-doping controls. Together with our partners and the National Anti-Doping Agency (NADA, associated), we are improving the privacy aspects of national athletes by introducing a privacy-enhancing anti-doping environment. More...



SPECIAL will allow citizens and organisations to share more data, while guaranteeing data protection compliance, thus enabling both trust and the creation of valuable new insights from shared data. Our vision will be realised and validated via real world use cases that - in order to be viable - need to overcome current challenges concerning the processing and sharing of data in a privacy preserving manner. In order to realise this vision, SPECIAL will combine and significantly extend big data architectures to handle Linked Data, harness them with sticky policies as well as scalable queryable encryption, and develop advanced user interaction and control features: SPECIAL will build on top of the Big Data Europe and PrimeLife Projects, exploit their results, and further advance the state of the art of privacy enhancing technologies. More...



Beierle, F. and Tran, V.T. and Allemand, M. and Neff, P. and Schlee, W. and Probst, T. and Pryss, R. and Zimmermann, J. (2018). TYDR - Track Your Daily Routine. Android App for Tracking Smartphone Sensor and Usage Data. 2018 ACM/IEEE 5th International Conference on Mobile Software Engineering and Systems (MOBILESoft '18). ACM, 72-75.

Link to publication

Beierle, F. and Tran, V.T. and Allemand, M. and Neff, P. and Schlee, W. and Probst, T. and Pryss, R. and Zimmermann, J. (2018). Context Data Categories and Privacy Model for Mobile Data Collection Apps. Procedia Computer Science. Elsevier (to appear).

Beierle, F. (2018). Do You Like What I Like? Similarity Estimation in Proximity-based Mobile Social Networks. Proceedings 2018 IEEE International Conference On Trust, Security And Privacy In Computing And Communications (TrustCom). IEEE (to appear).

Link to publication

Lüders, B. and Ruppel, P. (2018). Macroscopic Patterns in Sparse Location Data: Identifying Mobility Prototypes. Proceedings of the 4th IEEE International Conference on Big Data Service and Applications (BigDataService 2018)

Rieger, C. and Westerkamp, M and Kuchen, H. (2018). Challenges and Opportunities of Modularizing Textual Domain-Specific Languages. Proceedings of the 6th International Conference on Model-Driven Engineering and Software Development

Link to publication


Schanzenbach, M. and Zickau, S. (2017). Identity and Access Management in a Doping Control Use Case. Datenschutz und Datensicherheit - DuD

Göndör, S. (2017). The Importance of Data Portability and Interoperability in the Social Web. Practical Implementation of the Right to Data Portability - Legal, Technical and Consumer-Related Implications. Stiftung Datenschutz.

Herber, T. and Jentsch, M. and Zickau, S. (2017). Datenschutz und Dopingkontrollen. Datenschutz und Datensicherheit - DuD, 427-433.

Link to publication

Demchenko, Y. and Turkmen, F. and Slawik, M. and Laat, C. d. (2017). Defining Intercloud Security Framework and Architecture Components for Multi-cloud Data Intensive Applications. 2017 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID), 945-952.

Erdmann, J. and Rummel, J. and Wagner, P. (2017). SUMO and the German Handbook for the Dimensioning of Highways (HBS). SUMO 2017 – Towards Simulation for Autonomous Mobility. Deutsches Zentrum für Luft- und Raumfahrt e. V., 163-169.

Rummel, J. (2017). Replication of the HBS Autobahn with SUMO. SUMO 2017 – Towards Simulation for Autonomous Mobility. Deutsches Zentrum für Luft- und Raumfahrt e. V., 171-178.

Rodriguez Garzon, S. and Arbuzin, D. and Küpper, A. (2017). Geofence Index: A Performance Estimator for the Reliability of Proactive Location-based Services. Proceedings of the 18th IEEE International Conference on Mobile Data Management (IEEE MDM 2017). IEEE.

Beierle, F. and Aizawa, A. and Beel, J. (2017). Exploring Choice Overload in Related-Article Recommendations in Digital Libraries. Proceedings of the 5th International Workshop on Bibliometric-enhanced Information Retrieval (BIR2017). CEUR-WS, 51–61.

Link to publication

Friese, I. and Copeland, R. and Göndör, S. and Beierle, F. and Küpper, A. and Pereir, R. and Crom, J.-M. (2017). Cross-Domain Discovery of Communication Peers - Identity Mapping and Discovery Services (IMaDS). Proceedings of the 2017 European Conference on Networks and Communications (EuCNC). IEEE.

Link to publication

Beierle, F. and Grunert, K. and Göndör, S. and Schlüter, V. (2017). Towards Psychometrics-based Friend Recommendations in Social Networking Services. 2017 IEEE 6th International Conference on AI & Mobile Services (AIMS 2017). IEEE, 105–108.

Link to publication

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