Publications and Talks

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• Thorsten Peinemann, Moritz Kirschte, Joshua Stock, Carlos Cotrini, Esfandiar Mohammadi:
  S-BDT: Distributed Differentially Private Boosted Decision Trees.
  CCS '24: Proceedings of the 2024 on ACM SIGSAC Conference on Computer and Communications Security.
  
• Joshua Stock, Henry Heitmann, Janik Noel Schug, Daniel Demmler:
  DealSecAgg: Efficient Dealer-Assisted Secure Aggregation for Federated Learning.
  19th International Conference on Availability, Reliability and Security (ARES'24), July 30–August 02, 2024, Vienna, Austria.
  
• Joshua Stock, Lucas Lange, Erhard Rahm, Hannes Federrath:
  Property Inference as a Regression Problem: Attacks and Defense.
  21st International Conference on Security and Cryptography (SECRYPT'24), July 8-10, 2024, Dijon, France.
  
• Rosario Cammarota, Matthias Schunter, Anand Rajan, Fabian Boemer, Ágnes Kiss, Amos Treiber, Christian Weinert, Thomas Schneider, Emmanuel Stapf, Ahmad-Reza Sadeghi, Daniel Demmler, Joshua Stock, Huili Chen, Siam Umar Hussain, Sadegh Riazi, Farinaz Koushanfar, Saransh Gupta, Tajan Simunic Rosing, Kamalika Chaudhuri, Hamid Nejatollahi, Nikil Dutt, Mohsen Imani, Kim Laine, Anuj Dubey, Aydin Aysu, Fateme Sadat Hosseini, Chengmo Yang, Eric Wallace, Pamela Norton:
  Trustworthy AI Inference Systems: An Industry Research View.
  arXiv:2008.04449 (cs).
  
• Joshua Stock, Oliver Hauke, Julius Weißmann, Hannes Federrath:
  The Applicability of Federated Learning to Official Statistics.
  24th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL'23), November 22-24, 2023, Évora, Portugal.
  
• Johanna Ansohn McDougall, Alessandro Brighente, Willi Großmann, Ben Ansohn McDougall, Joshua Stock, Hannes Federrath:
  LoVe is in the Air – Location Verification of ADS-B Signals using Distributed Public Sensors.
  IEEE International Conference on Communications (ICC), May 28th - June 1st 2023, Rome, Italy.
  
• Tom Petersen, Joshua Stock, Hannes Federrath:
  Bedrohungsszenarien für Energieinfrastrukturen.
  Whitepaper im Rahmen des Norddeutschen Reallabors (NRL).
  
• Joshua Stock, Jens Wettlaufer, Daniel Demmler, Hannes Federrath:
  Lessons Learned: Defending Against Property Inference Attacks.
  20th International Conference on Security and Cryptography (SECRYPT'23), July 10-12, 2023, Rome, Italy.
  
• Joshua Stock, Tom Petersen, David Zadim, Hannes Federrath:
  Studie zur fachlichen Einschätzung und Prüfung des Potenzials von Federated-Learning-Algorithmen in der amtlichen Statistik.
  Abschlussbericht zur Studie im Auftrag des Statistisches Bundesamts (DESTATIS), Wiesbaden, 2023.
  
• Joshua Stock, Jens Wettlaufer, Daniel Demmler, Hannes Federrath:
  Lessons Learned: How (Not) to Defend Against Property Inference Attacks.
  arXiv:2205.08821 [cs.CR].
  
• Joshua Stock, Tom Petersen, Christian-Alexander Behrendt, Hannes Federrath, Thea Kreutzburg:
  Privatsphärefreundliches maschinelles Lernen - Teil 2: Privatsphäreangriffe und Privacy-Preserving Machine Learning.
  Informatik Spektrum 45/3 (2022).
  [Teil 1, Teil 2]
• Joshua Stock, Tom Petersen, Christian-Alexander Behrendt, Hannes Federrath, Thea Kreutzburg:
  Privatsphärefreundliches maschinelles Lernen - Teil 1: Grundlagen und Verfahren.
  Informatik Spektrum 45/2 (2022).
  [Teil 1, Teil 2]

12 items found.