CORE A/A* ranked venues marked in bold.

2024

Qi Pang, Jinhao Zhu, Helen Möllering, Wenting Zheng, and Thomas Schneider. BOLT: Privacy-preserving, accurate and efficient inference for transformers. In 45. IEEE Symposium on Security and Privacy (IEEE S&P'24), IEEE, San Francisco, CA, USA, May 20-23, 2024. To appear. Online: https://ia.cr/2023/1893. Acceptance rate 14.9%. CORE rank A*. [ web ]

Yaniv Ben-Itzhak, Helen Möllering, Benny Pinkas, Thomas Schneider, Ajith Suresh, Oleksandr Tkachenko, Shay Vargaftik, Christian Weinert, Hossein Yalame, and Avishay Yanai. ScionFL: Secure quantized aggregation for federated learning. In 2. IEEE Conference on Secure and Trustworthy Machine Learning (SaTML'24), IEEE, Toronto, Canada, April 9-11, 2024. To appear. Online: https://arxiv.org/abs/2210.07376. [ pdf | web ]

2023

Hannah Keller, Helen Möllering, Thomas Schneider, Oleksandr Tkachenko, and Liang Zhao. Secure noise sampling for DP in MPC with finite precision. Cryptology ePrint Archive, Report 2023/1594, October 17, 2023. https://ia.cr/2023/1594.

Helen Möllering. Towards Practical Privacy-Preserving Clustering and Health Care Data Analyses. PhD thesis, TU Darmstadt, Germany, September 29, 2023. [ pdf ]

2022

Daniel Günther, Marco Holz, Benjamin Judkewitz, Helen Möllering, Benny Pinkas, Thomas Schneider, and Ajith Suresh. POSTER: Privacy-preserving epidemiological modeling on mobile graphs. In 29. ACM Conference on Computer and Communications Security (CCS'22) Posters/Demos, pages 3351–3353, ACM, Los Angeles, USA, November 7-11, 2022. CORE rank A*. [ DOI | pdf | web ]

Timm Birka, Kay Hamacher, Tobias Kussel, Helen Möllering, and Thomas Schneider. SPIKE: Secure and Private Investigation of the Kidney Exchange problem. BMC Medical Informatics and Decision Making, 22(1):253, September 22, 2022. Online: https://arxiv.org/abs/2204.09937. Code: https://encrypto.de/code/PPKE. CORE rank B. [ DOI | pdf | web ]

Thien Duc Nguyen, Phillip Rieger, Huili Chen, Hossein Yalame, Helen Möllering, Hossein Fereidooni, Samuel Marchal, Markus Miettinen, Azalia Mirhoseini, Shaza Zeitouni, Farinaz Koushanfar, Ahmad-Reza Sadeghi, and Thomas Schneider. FLAME: Taming backdoors in federated learning. In 31. USENIX Security Symposium (USENIX Security'22), pages 1415–1432, USENIX, Boston, MA, USA, August 10-12, 2022. Online: https://ia.cr/2021/025. Acceptance rate 18.1%. CORE rank A*. [ pdf | web ]

2021

Aditya Hegde, Helen Möllering, Thomas Schneider, and Hossein Yalame. CONTRIBUTED TALK: SoK: Privacy-preserving clustering (Extended Abstract). Privacy in Machine Learning Workshop (PriML@NeurIPS'21), Virtual Event, December 14, 2021. [ web ]

Hannah Keller, Helen Möllering, Thomas Schneider, and Hossein Yalame. POSTER: Balancing quality and efficiency in private clustering with affinity propagation (Extended Abstract). 4. Privacy Preserving Machine Learning Workshop (PPML@CCS'21), Virtual Event, November 19, 2021. [ web ]

Aditya Hegde, Helen Möllering, Thomas Schneider, and Hossein Yalame. POSTER: SoK: Privacy-preserving clustering (Extended Abstract). 4. Privacy Preserving Machine Learning Workshop (PPML@CCS'21), Virtual Event, November 19, 2021. [ web ]

Timm Birka, Tobias Kussel, Helen Möllering, and Thomas Schneider. An efficient and practical privacy-preserving kidney exchange problem protocol (Abstract). In 33. Kryptotag (crypto day matters), Gesellschaft für Informatik e.V. / FG KRYPTO, Virtual Event, September 17, 2021. [ DOI | pdf ]

Sébastien Andreina, Giorgia Azzurra Marson, Helen Möllering, and Ghassan Karame. BaFFLe: Backdoor detection via feedback-based federated learning. In 41. IEEE International Conference on Distributed Computing Systems (ICDCS'21), IEEE, Virtual Event, July 7-10, 2021. CORE rank A. [ pdf | web ]

Hannah Keller, Helen Möllering, Thomas Schneider, and Hossein Yalame. Balancing quality and efficiency in private clustering with affinity propagation. In 18. International Conference on Security and Cryptography (SECRYPT'21), pages 173–184, SciTePress, Virtual Event, July 6-8, 2021. Full version: https://ia.cr/2021/825. Code: https://encrypto.de/code/ppAffinityPropagation. Acceptance rate 18.4% for full papers. CORE rank B. [ DOI | pdf | web ]

Aditya Hegde, Helen Möllering, Thomas Schneider, and Hossein Yalame. SoK: Efficient privacy-preserving clustering. Proceedings on Privacy Enhancing Technologies (PoPETs), 2021(4):225–248, July 2021. Online: https://ia.cr/2021/809. Code: https://encrypto.de/code/SoK_ppClustering. Acceptance rate 19.5%. CORE rank A. [ DOI | pdf | web ]

Beyza Bozdemir, Sébastien Canard, Orhan Ermis, Helen Möllering, Melek Önen, and Thomas Schneider. Privacy-preserving density-based clustering. In 16. ACM ASIA Conference on Computer and Communications Security (ASIACCS'21), pages 658–671, ACM, Virtual Event, June 7-11, 2021. Online: https://ia.cr/2021/612. Code: https://encrypto.de/code/ppDBSCAN. Acceptance rate 18.9%. CORE rank A. [ DOI | pdf | web ]

Hossein Fereidooni, Samuel Marchal, Markus Miettinen, Azalia Mirhoseini, Helen Möllering, Thien Duc Nguyen, Phillip Rieger, Ahmad-Reza Sadeghi, Thomas Schneider, Hossein Yalame, and Shaza Zeitouni. SAFELearn: Secure aggregation for private federated learning. In 4. Deep Learning and Security Workshop (DLS'21), pages 56–62, IEEE, Virtual Event, May 27, 2021. Full version: https://ia.cr/2021/386. Acceptance rate 40%. [ DOI | pdf | web ]

Hannah Keller, Helen Möllering, Thomas Schneider, and Hossein Yalame. Privacy-preserving clustering (Abstract). In 32. Kryptotag (crypto day matters), Gesellschaft für Informatik e.V. / FG KRYPTO, Virtual Event, January 15, 2021. [ DOI | pdf ]

2020

Daniel Günther, Marco Holz, Benjamin Judkewitz, Helen Möllering, Benny Pinkas, Thomas Schneider, and Ajith Suresh. Privacy-preserving epidemiological modeling on mobile graphs. Cryptology ePrint Archive, Report 2020/1546, December 11, 2020. https://ia.cr/2020/1546.

2019

Helen Möllering. Thwarting semantic backdoor attacks in privacy preserving federated learning. Master's thesis, Eurecom, France & University of Twente, Netherlands, August 28, 2019.

2016

Helen Möllering. Vergleich der Methoden zur Applikationsentwicklung für mobile Endgeräte mit einem Fallbeispiel unter iOS. Bachelor's thesis, Westfälische Wilhelms-Universität Münster, Germany, November 19, 2016.