News
Data protection-friendly big-data analyses
The analysis of large amounts of data enables numerous improvements - in the fight against climate change as well as in medicine. At the same time, today's big-data analysis possibilities create entirely new risks for people's privacy. If data from different sources is combined in the analysis, it is often possible to combine supposedly anonymous data to create personal profiles, with sometimes unforeseeable consequences for the people concerned. A new study by the Fraunhofer Institute for Secure Information Technology SIT therefore shows how big-data technologies can be used without harming the privacy of individuals. The study is aimed at users and developers of big data systems and is available for free download at https://www.sit.fraunhofer.de/reports/
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ATHENE researchers contribute to new BMBF project CYWARN
The Federal Ministry of Education and Research (BMBF) launches its support for consortium project “Strategie- und Technologie-Entwicklung zur medienübergreifenden Erstellung eines Cyber-Lagebilds und akteurspezifischen Kommunikation von Cyber-Warnmeldungen“, CYWARN, from 1 October set to last for 3 years, with 2 million euros. ATHENE researcher Prof Christian Reuter, head of the chair for Science and Technology for Peace and Security (PEASEC), will coordinate the joint between partners in research, development and application.
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APNIC blog discusses the recent proposal of ATHENE researchers to distribute the power of RPKI authorities
Internet infrastructure is still very vulnerable. Security enhancements such as Domain Name System Security Extensions (DNSSEC) and Resource Public Key Infrastructure (RPKI) are based on cryptographic signatures. While private keys should theoretically be held by the owners of domains and Internet name resources, they are outsourced to centralised authorities in practice. This bearsconsiderable security risks.
In his post, ATHENE researcher Kris Shrishak, TU Darmstadt, proposes a change to RPKI that will strengthen the threat model and prevent unilateral takedown of IP prefixes by Regional Internet Registries (RIRs).
How secure is Machine Learning?
The value of security and privacy in machine learning approaches has been investigated by researchers of the Fraunhofer Institute for Applied and Integrated Security AISEC, the Fraunhofer Institute for Secure Information Technology SIT, the National Research Center for Applied Cybersecurity ATHENE and the Freie Universität Berlin in a joined study. Participants who work professionally or personally with machine learning approaches are still needed for the research project.
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Counter-espionage solution for eavesdropping devices Alexa & Co.
Together with partners from the U.S. and France, an ATHENE research team with members from the TU Darmstadt has developed a device that can detect Smart Home devices that stream audio recordings on the Internet without permission via language assistance.
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