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  • Konrad Rieck
Logo Institut für Systemsicherheit der TU Braunschweig
  • Konrad Rieck
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Konrad Rieck

Prof. Dr. Konrad Rieck

Contact

Email
k.rieck (at) tu-bs.de (PGP)
Home Office
+49 151 512-65917
Telephone
+49 531 391-55120
Room
830 (8th floor; above 7½th floor)
Address
Technische Universität Braunschweig
Institute of System Security
Mühlenpfordtstraße 23
38106 Braunschweig, Germany

About me

I am a Professor of Computer Science at TU Braunschweig where I head the Institute of System Security. From 2019 to 2021, I have been the Dean of Studies for Computer Science. Previously, I have been working at the University of Göttingen, Technische Universität Berlin, 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. 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

Dos and Don'ts of Machine Learning in Computer Security.
Daniel Arp, Erwin Quiring, Feargus Pendlebury, Alexander Warnecke, Fabio Pierazzi, Christian Wressnegger, Lorenzo Cavallaro and Konrad Rieck.
Proc. of the 31st USENIX Security Symposium, to appear August 2022.

LaserShark: Establishing Fast, Bidirectional Communication into Air-Gapped Systems.
Niclas Kühnapfel, Stefan Preußler, Maximilian Noppel, Thomas Schneider, Konrad Rieck and Christian Wressnegger.
Proc. of the 37th Annual Computer Security Applications Conference (ACSAC), December 2021.

LogPicker: Strengthening Certificate Transparency Against Covert Adversaries.
Alexandra Dirksen, David Klein, Robert Michael, Tilman Stehr, Konrad Rieck and Martin Johns.
Proceedings on Privacy Enhancing Technologies (PETS), July 2021.

Evaluating Explanation Methods for Deep Learning in Computer Security.
Alexander Warnecke, Daniel Arp, Christian Wressnegger and Konrad Rieck.
Proc. of the 5th IEEE European Symposium on Security and Privacy (EuroS&P), September 2020.

Adversarial Preprocessing: Understanding and Preventing Image-Scaling Attacks in Machine Learning.
Erwin Quiring, David Klein, Daniel Arp, Martin Johns and Konrad Rieck.
Proc. of the 29th USENIX Security Symposium, August 2020.

A complete list of my publications is available here.

Awards

  • ERC Consolidator Grant 2021
  • AISEC Best Paper Award 2021
  • Winner of Microsoft MLSEC competition 2020
  • LehrLeo: Best Lecture at TU Braunschweig 2019
  • LehrLeo: Best Practical 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)
  • Scientific Advisory Board "IT Security" of Volkswagen AutoUni
  • 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—2022
  • 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
  • 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; IEEE SaTML
  • 2022: USENIX SEC; ACM CCS; RAID; DIMVA; DLS; 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;

A complete list of my academic services is available here.

Reviewing Statistics

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

Email Activity

I am also tracking my email activity. Here are two plots showing the number of incoming and outgoing emails over the last two weeks.

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)

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