Foto von Christoph Hofmeister

M.Sc. Christoph Hofmeister

Technische Universität München

Professur für Codierung und Kryptographie (Prof. Wachter-Zeh)

Postadresse

Postal:
Theresienstr. 90
80333 München

Biografie

  • Duales Studium bei Infineon Technologies (2015-2019)
  • B.Eng. in Elektro- und Informationstechnik, Hochschule München (2019)
  • M.Sc. in Elektro- und Informationstechnik, Technische Universität München (2021)
  • Seit Oktober 2021 Doktorand an der Lehr- und Forschungseinheit für Nachrichtentechnik, Professur für Coding und Kryptographie

Abschlussarbeiten

Angebotene Abschlussarbeiten

Private and Secure Federated Learning

Beschreibung

In federated learning, a machine learning model shall be trained on private user data with the help of a central server, the so-called federator. This setting differs from other machine learning settings in that the user data shall not be shared with the federator for privacy reasons and/or to decrease the communication load of the system.

Even though only intermediate results are shared, extra care is necessary to guarantee data privacy. An additional challenge arises if the system includes malicious users that breach protocol and send corrupt computation results.

The goal of this work is to design, implement and analyze coding- and information-theoretic solutions for privacy and security in federated learning.

Voraussetzungen

  • Coding Theory (e.g., Channel Coding)
  • Information Theory
  • Machine Learning Basics

Betreuer:

Laufende Abschlussarbeiten

A Framework for Federated Learning with Variable Local Updates

Beschreibung

Since the introduction of federated learning in [1], we can observe a rapidly growing body of research. In particular, we face challenges with respect to privacy, security and efficiency. We build upon an existing generic framework for simulating decentralized optimization procedures in a federated learning setting. With the help of that framework, the student should analyze the performance of selected state-of-the-art schemes and investigate different protocols that utilize local updates and the effect of straggling clients.

Betreuer:

Publikationen

2022

  • Christoph Hofmeister; Luis Maßny; Rawad Bitar; Eitan Yaakobi: Trading Communication and Computation for Security in Gradient Coding. Munich Workshop on Coding and Cryptography 2022, 2022 mehr…
  • Christoph Hofmeister; Luis Maßny; Rawad Bitar; Eitan Yaakobi: Trading Communication and Computation for Security in Gradient Coding. 2022 IEEE European School of Information Theory (ESIT), 2022 mehr…
  • Hofmeister Christoph; Luis Maßny; Rawad Bitar; Eitan Yaakobi: Trading Communication and Computation for Security in Gradient Coding. TUM ICE Workshop Raitenhaslach, 2022 mehr…
  • Hofmeister, Christoph; Bitar, Rawad; Xhemrishi, Marvin; Wachter-Zeh, Antonia: Secure Private and Adaptive Matrix Multiplication Beyond the Singleton Bound. IEEE Journal on Selected Areas in Information Theory 3 (2), 2022, 275-285 mehr… Volltext ( DOI )
  • Hofmeister, Christoph; Bitar, Rawad; Xhemrishi, Marvin; Wachter-Zeh, Antonia: Secure Private and Adaptive Matrix Multiplication Beyond the Singleton Bound. WCC 2022: The Twelfth International Workshop on Coding and Cryptography , 2022 mehr…