
FH-Prof. Priv.-Doz. MMag. Dr.
Günther Eibl
Forschungsgruppenleiter
Department Information Technologies and Digitalisation
Raum: Urstein - 421
Aktuelle Lehre
ITS-B | 2. SS 2026 | Mathematik 2 | IL
ITSB-B | 2. SS 2026 | Mathematik 2 | IL
Schwerpunkte
Lehre (50%)
- Mathematics
- Statistics
- Data Mining
Forschung (50%)
- Deputy head of the center for secure energy informatics
- Research interest: Privacy in the smart grid with 2 main parts
Privacy analyses
analyze the information that can be obtained from load profiles using primarily methods from machine learning, statisticsor whatever is useful
Privacy enhancing technologies
- Here, the focus in the past was on privacy-preserving data aggregation using homomorphic encryption, masking, differential privacy and wavelet analysis.
- Now the focus shifts to (i) tariffs and privacy-preserving price calculation and (ii) application of methods in order strictly proof privacy-preserving properties of proposed privacy-preserving protocols.
Publikationen:
- see https://scholar.google.de/citations?hl=de&user=n7TwAXcAAAAJ
- or http://www.en-trust.at/publications/
Ausbildung
- Magister in mathematics (numerics thesis)
- Magister in physics (plasma physics simulation thesis)
- Doktorat in machine learning (multiclass boosting thesis)
Aktuelle Forschungsprojekte
- FTZ CyberSec: Cybersecurity - FTZ für datenbasierte Evaluierung von Sicherheits- und Privacy-Technologien
Das Projektziel ist ein offener und breiter Wissenstransfer in den Bereichen KI-Sicherheit und Datenschutz für datenbasierte Geschäftsmodelle. Als...
04/2025 - 12/2028 - DAWN: Data-driven Analysis and Optimization of Low Voltage Networks
Der verstärkte Einsatz erneuerbarer Energieträger und der Wandel zur Elektromobilität führen zu einer größeren Volatilität im Energiesystem....
01/2025 - 12/2026 - Trampoline IT 24/25: Trampoline IT 24/25
Trampolin-Vorhaben des Departments IT 2024/25:2 Vorhaben: 1.) Brückenfinanzierung für Forschungs- und Transferzentrum (FTZ) "Cybersecurity"PI: Günther...
09/2024 - 08/2025
Aktuelle Publikationen
- Evaluating the Efficacy of LINDDUN GO for Privacy Threat Modeling for Local Renewable Energy Communities
While security is considered an essential aspect of the design and implementation of many systems, privacy is often overlooked, especially in early planning phases. Although methodologies for the...
2025 - Inferring the Hidden: Privacy Risks of Microaggregation in Smart Meter Data
2025 - Predicting Socio-Demographic Characteristics from Load Profiles with Varying Time Granularities
Energy consumption data from smart meters has been shown to infer socio-demographic characteristics, which impacts privacy. However, the impact of time granularity on the ability to classify such...
2025
Auszeichnungen
- Best Paper Award DACH+ Conference on Energy Informatics
30. Okt. 2020