News
CAST-Förderpreis IT-Sicherheit 2020 goes to ATHENE researcher
Daniel Günther from the TU Darmstadt won the first prize of the CAST-Förderpreis IT-Sicherheit in the category "Best Master Thesis" for his master thesis "Optimizing Private Information Retrieval for Compromised Credential Checking". He prevailed among the four finalists who presented their work to a jury of representatives from industry and research.
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Nationaler Pakt Cybersicherheit: Online Compendium Cybersecurity in Germany
Prof. Mira Mezini, together with Prof. Dr. Günter Krings, Parliamentary State Secretary at the Federal Ministry of the Interior, Building and Homeland Affairs, Claudia Nemat, Member of the Board of Management of Deutsche Telekom, and Klaus Müller, Board Member of the Federation of German Consumer Organisations (vzbv), presented today the online compendium Cyber Security in Germany to the public.
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AI helps to identify illegal cultural goods
Fraunhofer SIT press release (German):
Eine zentrale Herausforderung bei der Bekämpfung des illegalen Handels mit gestohlenen Kulturgütern besteht darin, dass illegal gehandelte Objekte nur schwer zu erkennen sind. Das von der Beauftragten der Bundesregierung für Kultur und Medien geförderte Projekt KIKu – KI für den Kulturgutschutz – hat zum Ziel, die Arbeit der zuständigen Akteure, insbesondere von Zoll und Polizei, zu erleichtern: Hierzu entwickelt das Fraunhofer-Institut für Sichere Informationstechnologie SIT gemeinsam mit der cosee GmbH eine App, die mit Hilfe von Künstlicher Intelligenz automatisiert Hinweise geben kann, ob beispielsweise eine antike Vase oder eine Statue aus einer Raubgrabung stammen könnte oder anders illegal erworben wurde. Das Projekt wurde gestern zahlreichen relevanten Akteuren auf dem Gebiet des Kulturgutschutzes aus Deutschland und der EU vorgestellt, die auf Einladung von Kulturstaatsministerin Monika Grütters zum 7. EU CULTNET-Treffen im Rahmen der deutschen EU-Ratspräsidentschaft zusammengekommen sind.
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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Best Paper Award for ATHENE researchers at the IEEE VizSec
ATHENE researchers of the Fraunhofer IGD were awarded the Best Paper Award at the IEEE Symposium on Visualization for Cyber Security (VizSec) for their publication "A Visualization Interface to Improve the Transparency of Collected Personal Data on the Internet". In their paper, the researchers* deal with the problem that Internet users lose track of the data they disclose and store due to the multitude of online services. The prototype they developed, TransparencyVis, supports users in gaining better control over their own data. Via https://transparency-vis.vx.igd.fraunhofer.de/, users can upload exports from Facebook, Google, Instagram and Twitter simultaneously or individually and explore them interactively.
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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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Best Paper Award for ATHENE researchers at ARES 2020
Oren Halvani, Lukas Graner and Roey Regev of the Fraunhofer SIT received the Best Paper Award at the Workshop Digital Forensics (WSDF2020) during the ARES conference 2020.
In their paper TAVeer – An Interpretable Topic-Agnostic Authorship Verification Method, they introduced an authorship verification process (AV) that reviews and verifies whether a specified person has in fact written an anonymous letter or rather confirms whether a text actually stems from the stated author. This is relevant for cases in suspicion of plagiarism for example.
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).
ATHENE researcher becomes part of ProProfessur promotion program
ATHENE researcher Dr Juliane Krämer of the TU Darmstadt was admitted to the subsidy program ProProfessur by Mentoring Hessen. The program supports and backs advanced researchers on their way to professorship.
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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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