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Lukas Burkhalter
Lukas Burkhalter

PhD Student

Lukas Burkhalter

I am fourth year Ph.D. student in the Applied Cryptography Group and the Privacy Preserving Systems Lab at ETH Zurich, where I am advised by Prof. Kenny Paterson and Dr. Anwar Hithnawi. I graduated from ETH Zurich in 2017 with a Master of Science in Computer Science. Before that, I did my B.Sc. studies at ETH Zurich. I design and build privacy-preserving systems that use cryptography to give users more control on how their data is shared and processed.

Awards

  • Microsoft Research EMEA PhD Award
  • ETH Medal for Master Thesis

Talks

TimeCrypt: Encrypted Data Stream Processing at Scale with Cryptographic Access.

  • ETH Zurich, Systems Lunch Seminar
  • Intel, Santa Clara, CA
  • USENIX NSDI, Santa Clara, CA, [Video, Slides]
  • UC Berkeley, CA, RISE Security Seminar
  • UC Berkeley, CA, NetSys Lunch Seminar

Zeph: Cryptographic Enforcement of End-to-End Data Privacy.

RoFL: Attestable Robustness for Secure Federated Learning

  • Data Centric AI Workshop, ETH Zurich, [Video]

Teaching:

  • Information Security Lab (2021)
  • Informatik II für D-ITET (2018-2020)
  • Informatik I für BAUG (2018)

Selected Publications:

Thumbnail of RoFL: Robustness of Secure Federated Learning

RoFL: Robustness of Secure Federated Learning Paper Slides Github Video

Hidde Lycklama*, Lukas Burkhalter*, Alexander Viand, Nicolas Küchler, Anwar Hithnawi

IEEE Security and Privacy (Oakland) 2023.

Thumbnail of VF-PS: How to Select Important Participants in Vertical Federated Learning, Efficiently and Securely?.

VF-PS: How to Select Important Participants in Vertical Federated Learning, Efficiently and Securely?. Paper

Jiawei Jiang, Lukas Burkhalter, Fangcheng Fu, Bolin Ding, Bo Du, Anwar Hithnawi, Bo Li, Ce Zhang

NeurIPS (Spotlight) 2022.

Thumbnail of Cryptographic Auditing for Collaborative Learning

Cryptographic Auditing for Collaborative Learning Paper Poster

Hidde Lycklama, Nicolas Küchler, Alexander Viand, Emanuel Opel, Lukas Burkhalter, Anwar Hithnawi

ML Safety Workshop at NeurIPS 2022

Thumbnail of Zeph: Cryptographic Enforcement of End-to-End Data Privacy.

Zeph: Cryptographic Enforcement of End-to-End Data Privacy. Paper Slides Github Video

Lukas Burkhalter*, Nicolas Küchler*, Alexander Viand, Hossein Shafagh, Anwar Hithnawi

USENIX OSDI 2021.

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Thumbnail of Droplet: Decentralized Authorization and Access Control for Encrypted Data Streams.

Droplet: Decentralized Authorization and Access Control for Encrypted Data Streams. Paper Slides Github Website Video

Hossein Shafagh, Lukas Burkhalter, Sylvia Ratnasamy, Anwar Hithnawi

USENIX Security 2020.

Thumbnail of TimeCrypt: Encrypted Data Stream Processing at Scale with Cryptographic Access Control.

TimeCrypt: Encrypted Data Stream Processing at Scale with Cryptographic Access Control. Paper Slides Github Website Video

Lukas Burkhalter, Anwar Hithnawi, Alexander Viand, Hossein Shafagh, Sylvia Ratnasamy

USENIX NSDI 2020.

Thumbnail of Robust Secure Aggregation for Privacy-Preserving Federated Learning with Adversaries

Robust Secure Aggregation for Privacy-Preserving Federated Learning with Adversaries Paper

Lukas Burkhalter, Alexander Viand, Matthias Lei, Hossein Shafagh, Anwar Hithnawi

Privacy Preserving Machine Learning Workshop (PPML), 2019.

Thumbnail of Towards Blockchain-based Auditable Storage and Sharing of IoT Data.

Towards Blockchain-based Auditable Storage and Sharing of IoT Data. Paper

Hossein Shafagh, Lukas Burkhalter, Anwar Hithnawi

ACM Cloud Computing Security Workshop (CCSW), Dallas, TX, USA, 2017.

Thumbnail of Secure Sharing of Partially Homomorphic Encrypted IoT Data.

Secure Sharing of Partially Homomorphic Encrypted IoT Data. Paper

Hossein Shafagh, Anwar Hithnawi, Lukas Burkhalter, Pascal Fischli, Simon Duquennoy

ACM SenSys 2017.