Prof. Dr. Konrad Rieck

Email

rieck@tu-berlin.de (PGP)

Telephone

+49 151 512-65917

Room

TEL 806 (above 7½th floor)

Address

Technische Universität Berlin
Machine Learning and Security, TEL 8-2
Ernst-Reuter-Platz 7
10587 Berlin, Germany

About me

I am a Professor of Computer Science at Technische Universität Berlin, where I head the Chair of Machine Learning and Security within the Berlin Institute for the Foundations of Learning and Data (BIFOLD). Previously, I have been working at Technische Universität Braunschweig, University of Göttingen, and Fraunhofer Institute FIRST.

My research interests revolve around computer security and machine learning. My group is developing novel methods for detecting computer attacks, analyzing malicious software and discovering security vulnerabilities. Moreover, we explore the security and privacy of learning algorithms. I am also interested in efficient algorithms for analyzing structured data, such as strings, trees, and graphs.

My Erdős number is 3 (Müller → Jagota → Erdős) and my Bacon number is ∞. I am a very distant academic relative of Carl Friedrich Gauß (see here), although this doesn't help when solving math problems.

Recent Publications

No more Reviewer #2: Subverting Automatic Paper-Reviewer Assignment using Adversarial Learning.
Thorsten Eisenhofer, Erwin Quiring, Jonas Möller, Doreen Riepel, Thorsten Holz and Konrad Rieck.
Proc. of the 32nd USENIX Security Symposium, 2023. (to appear)

PDF Code

Detecting Backdoors in Collaboration Graphs of Software Repositories.
Tom Ganz, Inaam Ashraf, Martin Härterich and Konrad Rieck.
Proc. of the 14th ACM Conference on Data and Applications Security and Privacy (CODASPY), 2023.

PDF

Machine Unlearning of Features and Labels.
Alexander Warnecke, Lukas Pirch, Christian Wressnegger and Konrad Rieck.
Proc. of the 30th Network and Distributed System Security Symposium (NDSS), 2023.

PDF Code

Improving Malware Detection with Explainable Machine Learning.
Michele Scalas, Konrad Rieck and Giorgio Giacinto.
Explainable Deep Learning AI: Methods and Challenges, Elsevier, 2023.

See all publications.

Awards

CCS Top Reviewer Award 2022
USENIX Security Distinguished Paper Award 2022
ERC Consolidator Grant 2021
AISEC Best Paper Award 2021
Winner of Microsoft MLSEC competition 2020
LehrLeo: Best Lecture at TU Braunschweig 2019
LehrLeo: Best Lab Course at TU Braunschweig 2019

DLS Outstanding Reviewer Award 2018
German Prize for IT-Security 2016 (2nd Place)
DIMVA Best Paper Award 2016
RAID Outstanding Reviewer Award 2015
Google Faculty Research Award 2014
ACSAC Outstanding Paper Award 2012
CAST/GI Dissertation Award IT-Security 2010

Academic Memberships

Steering committee of the IEEE Workshop on Deep Learning and Security (DLS)
Steering committee of the ACM Workshop on Robust Malware Analysis (WORMA)
Steering committee of the SIG SIDAR Conference DIMVA
Steering committee of the SIG Intrusion Detection and Response (SIDAR)
European Laboratory for Learning and Intelligent Systems (ELLIS)
BMBF Plattform Lernende Systeme: WG 3 IT Security, Privacy, Legal and Ethical Framework
Forum InformatikerInnen für Frieden und gesellschaftliche Verantwortung (FIfF)
Jury of the German IT Security Award 2022
Jury of CAST/GI Dissertation Award IT-Security 2016—2023
Jury of Dutch Cyber Security Research Paper Award 2018
Guest editor of the special issue "Vulnerability Analysis" in Information Technology 2016
Guest editor of the special issue "Threat Detection, Analysis and Defense" in JISA 2013
Editorial Board of the Journal of Machine Learning Research (JMLR) 2013—2019

Conference and Workshop Organization

Organizer, Dagstuhl Seminar Security of Machine Learning in 2022
PC chair, 2nd IEEE Workshop on Deep Learning and Security (DLS'19)
PC chair, 11th-12th ACM European Workshop on Systems Security (EUROSEC'18 & 19)
PC chair, 10th Conference on Detection of Intrusions and Malware (DIMVA'13)
PC chair, 6th European Conference on Computer Network Defense (EC2ND'10)
Local organizer, GI Graduate Workshop on Reactive Security (SPRING'06)

Recent PC Memberships

2023: IEEE S&P; USENIX SEC; ACM CCS; RAID; ACSAC; IEEE SATML; DIMVA; DLSP;
2022: USENIX SEC; ACM CCS; RAID; DIMVA; DLS; AISEC; MADWEB;
2021: IEEE S&P; USENIX SEC; ACM CCS; NDSS; RAID; DLS; AISEC; MADWEB; BAR; ROOTS;
2020: IEEE S&P; USENIX SEC; ACM CCS; NDSS; EUROSEC; DLS; AISEC; ROOTS;
2019: IEEE S&P; USENIX SEC; ACSAC; RAID; EUROS&P; SAC; SCAINET; EUROSEC; DLS;
2018: ACSAC; ICDCS; DIMVA; ASIACCS; SAC; EUROSEC; DLS; AISEC;
2017: ACSAC; DIMVA; ASIACCS; SAC; AISEC; EUROSEC; LASER; ROOTS;
2016: ACM CCS; ACSAC; RAID; EUROS&P; DIMVA; SAC; SEC; AISEC; EUROSEC;

Review and Email Activity

For fun, I am tracking my reviewing and email activity. Here are two plots showing my reviewing activity over the last years. As you can see, I am writing a lot of reviews per year. Most of the time, this is fun.

Similarly, here are two plots showing the number of incoming and outgoing emails on my university account over the last two weeks. The average and standard deviation are calculated over several years (see week number in legend).

Influential Security Papers

I am maintaining a list of top-cited security papers. The list is automatically created based on citations of papers published at the four tier-1 security conferences.

Whenever Possible

I am a member of "Verband der krawattenlosen Wissensträger" (VDKW)