Thorsten Eisenhofer

ML & Computer Security


About Me


I am a postdoctoral researcher at TU Berlin where I work in the Machine Learning and Security group of Konrad Rieck. Before that, I completed my PhD at the Ruhr University Bochum in the Systems Security group of Thorsten Holz. During my PhD, I was a security researcher in the DFG Cluster of Excellence “Cyber Security in the Age of Large-Scale Adversaries“ (CASA).

My research focus is on two fundamental aspects, machine learning and computer security, which I aim to investigate from a systems security perspective. By considering the learning algorithm as a part of a larger system, I study the increased attack surface of practical systems, but also analyze how such systems can be secured. I am further interested to investigate how learning-based approaches can be used to solve problems in computer security.

Along the way, I was interning in the SecLab at UC Santa Barbara working with Giovanni Vigna and Christopher Kruegel on symbolic execution and played with Shellphish at the DEF CON CTF finals in Las Vegas. More recently, I was visiting the Cleverhans Lab at the Vector Institute working with Nicolas Papernot on secure and trustworthy machine learning.

I obtained a B.Sc. in Computer Science from Paderborn University and a M.Sc. in Computer Security from Ruhr University Bochum. For my master studies, I was awarded best student in graduating class.

For questions, discussions or collaborations, feel free to reach out.


Publications


2024

Jonathan Evertz, Merlin Chlosta, Lea Schönherr, and Thorsten Eisenhofer

Whispers in the Machine: Confidentiality in LLM-integrated Systems

Computing Research Repository (CoRR)
[pdf] [code]

Joel Frank, Franziska Herbert, Jonas Ricker, Lea Schönherr, Thorsten Eisenhofer, Asja Fischer, Markus Dürmuth, and Thorsten Holz

A Representative Study on Human Detection of Artificially Generated Media Across Countries

Symposium on Security and Privacy (S&P)
[pdf] [preregistration] [code]

2023

Thorsten Eisenhofer

Security of Machine Learning Systems

Dissertation
[pdf] [slides]

Thorsten Eisenhofer, Erwin Quiring, Jonas Möller, Doreen Riepel, Thorsten Holz, and Konrad Rieck

No more Reviewer #2: Subverting Automatic Paper-Reviewer Assignment using Adversarial Learning

USENIX Security Symposium
[pdf] [slides] [examples] [code]

Hojjat Aghakhani, Lea Schönherr, Thorsten Eisenhofer, Dorothea Kolossa, Thorsten Holz, Christopher Kruegel, and Giovanni Vigna

VenoMave: Targeted Poisoning Against Speech Recognition

Conference on Secure and Trustworthy Machine Learning (SaTML)
[pdf] [code]

Nico Schiller, Merlin Chlosta, Moritz Schloegel, Nils Bars, Thorsten Eisenhofer, Tobias Scharnowski, Felix Domke, Lea Schönherr, and Thorsten Holz

Drone Security and the Mysterious Case of DJI's DroneID

Network and Distributed System Security Symposium (NDSS)
[pdf] [code]

David Pape, Sina Däubener, Thorsten Eisenhofer, Antonio Emanuele Cinà, and Lea Schönherr

On the Limitations of Model Stealing with Uncertainty Quantification Models

European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN)
[pdf]

2022

Thorsten Eisenhofer, Doreen Riepel, Varun Chandrasekaran, Esha Ghosh, Olga Ohrimenko, and Nicolas Papernot

Verifiable and Provably Secure Machine Unlearning

Computing Research Repository (CoRR)
[pdf] [code]

Roei Schuster, Jin Peng Zhou, Thorsten Eisenhofer, Paul Grubbs, and Nicolas Papernot

Learned Systems Security

Computing Research Repository (CoRR)
[pdf]

Michel Abdalla, Thorsten Eisenhofer, Eike Kiltz, Sabrina Kunzweiler, and Doreen Riepel

Password-Authenticated Key Exchange from Group Actions

Annual International Cryptology Conference (CRYPTO)
[pdf]

Lea Schönherr, Maximilian Golla, Thorsten Eisenhofer, Jan Wiele, Dorothea Kolossa, and Thorsten Holz

Exploring Accidental Triggers of Smart Speakers

Computer Speech & Language (CSL)
[pdf] [website]

2021

Thorsten Eisenhofer, Lea Schönherr, Joel Frank, Lars Speckemeier, Dorothea Kolossa, and Thorsten Holz

Dompteur: Taming Audio Adversarial Examples

USENIX Security Symposium
[pdf] [talk] [slides] [code]

2020

Joel Frank, Thorsten Eisenhofer, Lea Schönherr, Asja Fischer, Dorothea Kolossa, and Thorsten Holz

Leveraging Frequency Analysis for Deep Fake Image Recognition

International Conference on Machine Learning (ICML)
[pdf] [slides] [code]

Lea Schönherr, Thorsten Eisenhofer, Steffen Zeiler, Thorsten Holz, and Dorothea Kolossa

Imperio: Robust Over-the-Air Adversarial Examples for Automatic Speech Recognition Systems

Annual Computer Security Applications Conference (ACSAC)
[pdf] [talk] [examples]


Selected Talks




Teaching


Instructor

  • Privacy and Security in Learning, TU Berlin
    Master・Seminar・Summer 2024

  • Security Playground for Generative Agents, TU Berlin
    Master・Hands-on class・Summer 2024

  • ML & Computer Security, Ruhr University Bochum
    Master・Hands-on class・Winter 2021/22

  • ML & Computer Security, Ruhr University Bochum
    Master・Hands-on class・Summer 2021

  • ML & Computer Security, Ruhr University Bochum
    Master・Hands-on class・Winter 2020/21

Teaching Assistant

  • System Security, Saarland University
    Bachelor・Lecture・Summer 2021

  • System Security, Ruhr University Bochum
    Bachelor・Lecture・Summer 2020

  • Operating System Security, Ruhr University Bochum
    Master・Lecture・Winter 2019/20

  • System Security, Ruhr University Bochum
    Bachelor・Lecture・Summer 2019


News Coverage


Drone Security

Accidental Trigger