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Publications

Papers

2022

  1. Marc Rivinius, Pascal Reisert, Daniel Rausch, and Ralf Küsters: Publicly Accountable Robust Multi-Party Computation. In 2022 IEEE Symposium on Security and Privacy, SP 2022, San Francisco, CA, US, May 22-26, pp. 2430-2449.
    Conference Version   Technical Report   Slides   Recording

  2. Pascal Reisert, Marc Rivinius, Toomas Krips, and Ralf Kuesters: Arithmetic Tuples for MPC. In Cryptology ePrint Archive, Paper 2022/667.
    Technical Report

  3. David Mestel, Johannes Müller, and Pascal Reisert: How Efficient are Replay Attacks against Vote Privacy? A Formal Quantitative Analysis. In 35th IEEE Computer Security Foundations Symposium, CSF 2022, Haifa, Israel, August 7-10, pp. 179-194.
    Conference Version   Technical Report

  4. Natasha Fernandes, Annabelle McIver, Catuscia Palamidessi, and Ming Ding: Universal Optimality and Robust Utility Bounds for Metric Differential Privacy. In 35th IEEE Computer Security Foundations Symposium, CSF 2022, Haifa, Israel, August 7-10, pp. 348-363.
    Conference Version   Technical Report

  5. Nicolas Huber, Ralf Küsters, Toomas Krips, Julian Liedtke, Johannes Müller, Daniel Rausch, Pascal Reisert, and Andreas Vogt: Kryvos: Publicly Tally-Hiding Verifiable E-Voting. In Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security, CCS 2022, Los Angeles, CA, USA, November 7-11, pp. 1443-1457.
    Conference Version   Technical Report

  6. Filippo Galli, Sayan Biswas, Gangsoo Zeong, Tommaso Cucinotta, and Catuscia Palamidessi: Group privacy for personalized federated learning. International Workshop on Federated Learning: Recent Advances and New Challenges, in Conjunction with NeurIPS 2022, FL-NeurIPS'22, New Orleans, LA, USA, December 2.
    Workshop Version   Technical Report

  7. Mayar Elfares, Zhiming Hu, Pascal Reisert, Andreas Bulling, and Ralf Küsters: Federated Learning for Appearance-based Gaze Estimation in the Wild. In Proceedings of the 1st NeurIPS Gaze Meets ML Workshop / Proceedings of Machine Learning Research (Volume 210), GMML/PMLR 2022, New Orleans, LA, USA, December 3, pp. 20-36.
    Workshop Version   Technical Report

2023

  1. Divi De Lacour, Marc Lacoste, Mario Südholt, and Jacques Traoré: Towards Scalable Resilient Federated Learning: A Fully Decentralised Approach. Workshop on Pervasive and Resource-constrained AI, PeRConAI 2023, Atlanta, Georgia, USA, March 13-17, pp. 621-627
    Workshop Version   Poster (at DATAIA Workshop FL-Day)

  2. Konstantinos Chatzikokolakis, Giovanni Cherubin, Catuscia Palamidessi, and Carmela Troncoso: Bayes Security: A Not So Average Metric. In 36th IEEE Computer Security Foundations Symposium, CSF 2023, Dubrovnik, Croatia, July 9-13, pp. 159-177.
    Technical Report

  3. Pascal Reisert, Marc Rivinius, Toomas Krips, and Ralf Küsters: Overdrive LowGear 2.0: Reduced-Bandwidth MPC without Sacrifice. In Proceedings of the 2023 ACM Asia Conference on Computer and Communications Security, ASIACCS 2023, Melbourne, Australia, July 10-14, pp. 372-386.
    Conference Version   Technical Report

  4. Marc Rivinius, Pascal Reisert, Sebastian Hasler, and Ralf Küsters: Convolutions in Overdrive: Maliciously Secure Convolutions for MPC. In Proceedings on Privacy Enhancing Technologies 2023(3) / 23rd Privacy Enhancing Technologies Symposium, PoPETs/PETS 2023, Lausanne, Switzerland and Online, July 10-15, pp. 321-353.
    Journal Version   Technical Report   Slides   Code

Talks

2022

  1. Bastien Vialla: CRYPTECS. Video Presentation at the Workshop interdisciplinaire sur la sécurité globale, WISG 2022, Online, January 26-26.
    Video

  2. Catuscia Palamidessi: Differential Privacy: From the Central Model to the Local Model and their Generalization. Invited talk at the Collège de France, Sécurité du logiciel: quel rôle pour les langages de programmation? 2022, Paris, France, March 24.
    Slides   Recording

  3. Sven Trieflinger: Carbyne Stack – Open-source cloud-native Secure Multiparty Computation. Invited talk at Workshop on Theory and Practice of Multi-Party Computation, TPMPC 2022, Aarhus, Denmark, June 7-10.
    Abstract   Slides (access restricted)   Recording

  4. Sven Trieflinger: Carbyne Stack - Cloud Native Computing on Encrypted Data. Contributed talk at Emerging OS Forum, Open Source Summit North America 2022, OSS-NA 2022, Austin, Texas, USA, June 21-24.
    Abstract   Slides

  5. Sven Trieflinger: Scaling the Grail - Cloud-Native Computing on Encrypted Data using Carbyne Stack. Invited talk at StackConf '22, Berlin, Germany, July 19-22.
    Abstract   Recording

  6. Catuscia Palamidessi: Information Structures for Privacy and Fairness. Keynote at the Federated Logic Conference, FLoC 2022, Haifa, Israel, July 31-August 12.
    Recording

  7. Sven Trieflinger: One year of Carbyne Stack - Retrospective and Outlook. Contributed talk at CarbyneStackCon 2022, Stuttgart, Germany, October 27.
    Abstract   Recording

  8. Vincent Rieder: Cost-effective MPC from an offline phase with low communication. Contributed talk at CarbyneStackCon 2022, Stuttgart, Germany, October 27.
    Abstract   Recording

  9. Pascal Reisert: Generalized Tuples for MP-SPDZ. Contributed talk at CarbyneStackCon 2022, Stuttgart, Germany, October 27.
    Abstract   Recording

2023

  1. Felix Schuster: Introduction to confidential computing. Keynote at the Open Confidential Computing Conference 2023, OC3 2023, Online, March 15.
    Recording

  2. Malte Poll and Moritz Eckert: Wrapping entire Kubernetes clusters into a confidential-computing envelope with Constellation. Contributed talk at the Open Confidential Computing Conference 2023, OC3 2023, Online, March 15.
    Recording   Slides

  3. Sven Trieflinger: Nettle - Privacy-Preserving FL based on Flower and Carbyne Stack. Contributed talk at Flower Summit 2023, Cambridge, United Kingdom, May 30-31.
    Recording

Software

2021

  1. Robert Bosch GmbH: Carbyne Stack - Cloud Native Secure Multiparty Computation Platform.
    Website   GitHub Organization

2023

  1. Orange S.A.: Cryptecs/GPSGhoster. Demonstrator of an Android App with Differential Privacy for Geolocalization.
    Code

  2. Edgeless Systems GmbH: Constellation - Always Encrypted Kubernetes.
    Code

  3. Robert Bosch GmbH: Nettle - Flower-based Privacy-Preserving Federated Learning with secure aggregation using Carbyne Stack.
    Code

Miscellaneous

2021

  1. Sebastian Becker and Sven Trieflinger: Open Source Cloud Native Secure Multiparty Computation. Virtual Booth at MPC Alliance Data Privacy & Security Conference, Virtual, October 26, 2021.
    Website   Tutorial (requires registration)

2022

  1. Jan Paul Reimann: Secure Multiparty Computation – die Technologie der Zukunft. Newspaper Report in Tagespiegel Background, November 28, 2022.
    Article (German)
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