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SBA Research is a research center for Information Security
funded partly by the national initiative for COMET Competence Centers for Excellent Technologies.

Tag: CORE

1st Working Group Meeting on Sustainability & Computer Science @OCG

On December 2, 2025, the OCG Working Group on Sustainability & Computer Science marked the beginning of a new phase of collaboration with an interdisciplinary and transdisciplinary kick-off meeting. Chaired by Kevin Mallinger, lead of the CORE Research Group at SBA Research, the meeting focused on the central theme “AI and Farming” – an area where sustainable computing has the potential to create significant impact... Read More
working group members sitting around a table and discussing

New Article in MDPI Machine Learning and Knowledge Extraction

Our colleague Sebastian Raubitzek, researcher at SBA Research and a member of the Security and Privacy Research Group at the University of Vienna, has published a journal article titled Classification of Obfuscation Techniques in LLVM IR: Machine Learning on Vector Representations in MDPI's journal Machine Learning and Knowledge Extraction. ... Read More
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New paper in Science Computers and Electronics in Agriculture

Our colleagues Georg Goldenits, and Thomas Neubauer published a new paper on Taxonomy of cybersecurity consideration in agriculture. This paper explores the key cybersecurity threats and reliability risks in Agriculture 4.0 by mapping potential faults and pitfalls to emerging digital technologies in farming. It also discusses countermeasures, legal frameworks,… Read More
elsevier cover

New article in Big Data and Cognitive Computing

Our colleagues Philip König, Sebastian Raubitzek, Dennis Toth, Fabian Obermann and Kevin Mallinger published a new paper on Boost-Classifier-Driven Fault Prediction Across Heterogeneous Open-Source Repositories. In this paper they analyzed over 2.4 million commits from 33 open-source projects… Read More
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New Journal Article by Sebastian Raubitzek!

Sebastian Raubitzek, researcher at SBA Research, published an interesting journal article titled “Quantum-Inspired Kernel Matrices: Exploring Symmetry in Machine Learning“ in Physics Letters A via ScienceDirect by ELSEVIER. This insightful article explores how quantum principles can inspire new approaches… Read More
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Interesting Talk @ CGIAR

Sebastian Raubitzek and Kevin Mallinger have been invited for a special research seminar in CGIAR (Consultative Group on International Agricultural Research) about the application of complexity science in Artificial Intelligence. The talk focused on the possibility to enhance AI capacities for sustainability and productivity… Read More

This Abstract Was Written by ChatGPT: Empowering Intellectual Workers Through AI-Generated Content

With this we explore the transformative potential of AI in facilitating interdisciplinary research, enhancing learning experiences, and reducing academic workload. It delves into specific AI-driven tools that can democratize knowledge access, benefit both generalists and specialists, and streamline administrative tasks. The presentation aims to stimulate discussions on responsibly harnessing AI… Read More

On the Applicability of Quantum Machine Learning

This article shows the applicability of both classical and quantum machine learning algorithms on several data sets. Here, the authors developed one of the data sets based on quantum mechanical symmetry properties. The results show that classical machine learning algorithms still perform best in terms of accuracy and runtime, even… Read More