News
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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