Thorsten Eisenhofer
ML & Computer Security
I am a 4th year Ph.D. Student at Ruhr University Bochum working with Thorsten Holz. I am a security researcher in the DFG Cluster of Excellence “Cyber Security in the Age of Large-Scale Adversaries“ (CASA).
My research revolves around the intersection of machine learning and computer security. I am interested in adversarially robust speech recognition, detection of deep fake images, and in general on the security properties of learning algorithms in adversarial settings.
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 am currently a visiting researcher in 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.
Michel Abdalla, Thorsten Eisenhofer, Eike Kiltz, Sabrina Kunzweiler, and Doreen Riepel
Password-Authenticated Key Exchange from Group Actions
Annual International Cryptology Conference (CRYPTO)
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Lea Schönherr, Maximilian Golla, Thorsten Eisenhofer, Jan Wiele, Dorothea Kolossa, and Thorsten Holz
Thorsten Eisenhofer, Lea Schönherr, Joel Frank, Lars Speckemeier, Dorothea Kolossa, and Thorsten Holz
Dompteur: Taming Audio Adversarial Examples
USENIX Security Symposium (USENIX)
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[talk]
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Hojjat Aghakhani, Lea Schönherr, Thorsten Eisenhofer, Dorothea Kolossa, Thorsten Holz, Christopher Kruegel, and Giovanni Vigna
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)
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[slides]
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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)
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Instructor
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
Program Commitee
Accidental Trigger
Ruhr University Bochum: «When Speech Assistants Listen Even Though They Shouldn't» (EN)
NDR: «Wenn der smarte Lautsprecher mit dem Tatort-Kommissar spricht» (DE)
Süddeutsche Zeitung: «Wenn Alexa aus Versehen lauscht» (DE)
STRG_F: «Sex, Streit, Arztgespräche: wie oft Smart Speaker heimlich mithören» (DE)
tagesschau.de: «Die lauschenden Lautsprecher» (DE)
Tagesthemen: «Sprachassistenten hören mit» (DE)
Ars Technica: «Uncovered: 1,000 phrases that incorrectly trigger Alexa, Siri, and Google...» (EN)
ZDF logo!: «Hat Siri schlechte Ohren?» (DE)
detektor.fm: «Alexa, spionierst du mich aus?» (DE)
Fast Company: «Tired of Saying 'Hey Google' and 'Alexa'? Change it Up with These...» (EN)
Mitteldeutsche Rundfunk: «Wann hören Sprachassistenten mit?» (DE)
The Times: «Not in Front of the Speaker! Words that Wake Up Alexa» (EN)
Voicebot.ai: «More Than 1,000 Phrases Will Accidentally Awaken Alexa, Siri, and Google...» (EN)
Hessischer Rundfunk: «Immer ganz Ohr – Lauschangriff der Sprachassistenten» (DE)
Max Planck Society: «Uninvited Listeners in Your Speakers» (EN)
Remote Chaos Experience: «Alexa, Who Else Is Listening?» (EN)
Tech Conversationalist: «Are You Accidentally 'Waking Up' Your Smart Devices?» (EN)
hackster.io: «Incorrect Alexa, Siri, Google Assistant, and Cortana Trigger Words Are...» (EN)
Sputnik International: «‘Alarming’: Research Identifies Over 1,000 Phrases That Trick,...» (EN)
Mimikama: «Wenn Sprachassistenten zuhören, obwohl sie gar nicht sollen!» (DE)
Deep Fake Detection
Ruhr University Bochum: «Fake-Bilder anhand von Frequenzanalysen erkennen» (DE)
Homeland Security News Wire: «Using Frequency Analysis to Recognize Fake Images» (EN)
ElectronicsWeekly.com: «Frequency Analysis can Help Reveal Deep Fake Images» (EN)
Lab Manager: «Recognizing Fake Images Using Frequency Analysis» (EN)
SciTechDaily: «Which Face is Real? Using Frequency Analysis to Identify “Deep-Fake” Images» (EN)
Spektrum.de: «Mathematische Analyse soll alle Deep Fakes enttarnen» (DE)
VDI nachrichten: «Frequenzanalyse enttarnt Fake-Bilder» (DE)
INGENIEUR.de: «Social Media: Mit Frequenzanalysen Deep Fakes auf der Spur» (DE)
INDUSTRY OF THINGS: «Fake-Bilder anhand von Frequenzanalysen erkennen» (DE)
ZDF logo!: «Erkennt Greta Deep Fakes?» (DE)
Adversarially Robust Speech Recognition
RUBIN: «Wie Sprachassistenten unhörbare Befehle befolgen» (DE)
elektroniknet.de: «Angriffe auf Spracherkennungssoftware Kaldi» (DE)
Tech Xplore: «How Voice Assistants follow Inaudible Commands» (EN)
INGENIEUR.de: «Alexa, Siri und Co. – sicherer dank Training» (DE)
sg.hu: «Kivédhető a virtuális asszisztensek manipulálása» (HU)
Ruhr Unversity Bochum: «Die Forschungsreise „Möglichmacher“ legt Halt in Bochum ein» (DE)
WAZ: «IT-Sicherheit heißt: Immer einen Schritt voraus zu sein» (DE)