The following publications have been authored by members of the institute. We believe in open access and provide PDF files for almost all of these publications. The PDF files are preprints and we recommend visting the webpage of the publisher to obtain the original publication.
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), to appear February 2023.
Improving Malware Detection with Explainable Machine Learning.
Michele Scalas, Konrad Rieck and Giorgio Giacinto.
Explainable Deep Learning AI: Methods and Challenges, Elsevier, January 2023.
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, August 2022.
Distinguished Paper Award
I still know it's you! On Challenges in Anonymizing Source Code.
Micha Horlboge, Erwin Quiring, Roland Meyer and Konrad Rieck.
Technical report, arXiv:2208.12553, August 2022.
Quantifying the Risk of Wormhole Attacks on Bluetooth Contact Tracing.
Stefan Czybik, Daniel Arp and Konrad Rieck.
Proc. of the 13th ACM Conference on Data and Applications Security and Privacy (CODASPY), 264–275, April 2022.
Misleading Deep-Fake Detection with GAN Fingerprints.
Vera Wesselkamp, Konrad Rieck, Daniel Arp and Erwin Quiring.
Proc. of the 5th IEEE Workshop on Deep Learning and Security (DLS), 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.
Explaining Graph Neural Networks for Vulnerability Discovery.
Tom Ganz, Martin Härterich, Alexander Warnecke and Konrad Rieck.
Proc. of the 14th ACM Workshop on Artificial Intelligence and Security (AISEC), November 2021.
Best Paper Award
Spying through Virtual Backgrounds of Video Calls.
Jan Hilgefort, Daniel Arp and Konrad Rieck.
Proc. of the 14th ACM Workshop on Artificial Intelligence and Security (AISEC), November 2021.
Machine Unlearning of Features and Labels.
Alexander Warnecke, Lukas Pirch, Christian Wressnegger and Konrad Rieck.
Technical report, arXiv:2108.11577, August 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.
TagVet: Vetting Malware Tags using Explainable Machine Learning.
Lukas Pirch, Alexander Warnecke, Christian Wressnegger and Konrad Rieck.
Proc. of the 14th ACM European Workshop on Systems Security (EuroSec), 2021.
Explanation-driven Characterisation of Android Ransomware.
Michele Scalas, Konrad Rieck and Giorgio Giacinto.
Proc. of Workshop on Explainable Deep Learning/AI, December 2020.
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.
Technical report, arXiv:2010.09470, October 2020.
Against All Odds: Winning the Defense Challenge in an Evasion Competition with Diversification.
Erwin Quiring, Lukas Pirch, Michael Reimsbach, Daniel Arp and Konrad Rieck.
Technical report, arXiv:2010.09569, October 2020.
Evaluating Explanation Methods for Deep Learning in 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.
Backdooring and Poisoning Neural Networks with Image-Scaling Attacks.
Erwin Quiring and Konrad Rieck.
Proc. of the 3rd IEEE Workshop on Deep Learning and Security (DLS), May 2020.
What's All That Noise: Analysis and Detection of Propaganda on Twitter.
Ansgar Kellner, Christian Wressnegger and Konrad Rieck.
Proc. of the 13th ACM European Workshop on Systems Security (EuroSec), April 2020.
Political Elections Under (Social) Fire? Analysis and Detection of Propaganda on Twitter.
Ansgar Kellner, Lisa Rangosch, Christian Wressnegger and Konrad Rieck.
Technical report, arXiv:1912.04143, November 2019.
On the Security and Applicability of Fragile Camera Fingerprints.
Erwin Quiring, Matthias Kirchner and Konrad Rieck.
Proc. of the 24th European Symposium on Research in Computer Security (ESORICS), 450–470, September 2019.
Evaluating Explanation Methods for Deep Learning in Security.
Alexander Warnecke, Daniel Arp, Christian Wressnegger and Konrad Rieck.
Technical report, arXiv:1906.02108, September 2019.
Thieves in the Browser: Web-based Cryptojacking in the Wild.
Marius Musch, Christian Wressnegger, Martin Johns and Konrad Rieck.
Proc. of 14th International Conference on Availability, Reliability and Security (ARES), August 2019.
Best Paper Award Runner-Up
Misleading Authorship Attribution of Source Code using Adversarial Learning.
Erwin Quiring, Alwin Maier and Konrad Rieck.
Proc. of the 28th USENIX Security Symposium, August 2019.
False Sense of Security: A Study on the Effectivity of Jailbreak Detection in Banking Apps.
Ansgar Kellner, Micha Horlboge, Konrad Rieck and Christian Wressnegger.
Proc. of the 4th IEEE European Symposium on Security and Privacy (EuroS&P), June 2019.
TypeMiner: Recovering Types in Binary Programs using Machine Learning.
Alwin Maier, Hugo Gascon, Christian Wressnegger and Konrad Rieck.
Proc. of the 16th Conference on Detection of Intrusions and Malware & Vulnerability Assessment (DIMVA), 288–308, June 2019.
New Kid on the Web: A Study on the Prevalence of WebAssembly in the Wild.
Marius Musch, Christian Wressnegger, Martin Johns and Konrad Rieck.
Proc. of the 16th Conference on Detection of Intrusions and Malware & Vulnerability Assessment (DIMVA), 23–42, June 2019.
Best Paper Award Runner-Up
Proceedings of 2nd IEEE Deep Learning and Security Workshop (DLS).
Konrad Rieck and Battista Biggio (Eds.)
IEEE, May 2019.
Proceedings of 12th ACM European Workshop on Systems Security (EuroSec).
Konrad Rieck and Lorenzo Cavallaro (Eds.)
ACM, March 2019.
Security Analysis of Devolo HomePlug Devices.
Rouven Scholz and Christian Wressnegger.
Proc. of the 12th ACM European Workshop on Systems Security (EuroSec), March 2019.
Reading Between The Lines: Content-Agnostic Detection of Spear-Phishing Emails.
Hugo Gascon, Steffen Ullrich, Benjamin Stritter and Konrad Rieck.
Proc. of the 21st Symposium on Research in Attacks, Intrusions, and Defenses (RAID), September 2018.
Adversarial Machine Learning Against Digital Watermarking.
Erwin Quiring and Konrad Rieck.
Proc. of the 26th European Signal Processing Conference (EUSIPCO), September 2018.
Privacy-Enhanced Fraud Detection with Bloom filters.
Daniel Arp, Erwin Quiring, Tammo Krueger, Stanimir Dragiev and Konrad Rieck.
Proc. of the 14th International Conference on Security and Privacy in Communication Networks (SECURECOMM), August 2018.
Web-based Cryptojacking in the Wild.
Marius Musch, Christian Wressnegger, Martin Johns and Konrad Rieck.
Technical report, arXiv:1808.09474, August 2018.
ZOE: Content-based Anomaly Detection for Industrial Control Systems.
Christian Wressnegger, Ansgar Kellner and Konrad Rieck.
Proc. of the 48th Conference on Dependable Systems and Networks (DSN), 127–138, June 2018.
Forgotten Siblings: Unifying Attacks on Machine Learning and Digital Watermarking.
Erwin Quiring, Daniel Arp and Konrad Rieck.
Proc. of the 3rd IEEE European Symposium on Security and Privacy (EuroS&P), April 2018.
Proceedings of 11th ACM European Workshop on Systems Security (EuroSec).
Angelos Stavrou and Konrad Rieck (Eds.)
ACM, April 2018.
When Coding Style Survives Compilation: De-anonymizing Programmers from Executable Binaries.
Aylin Caliskan, Fabian Yamaguchi, Edwin Tauber, Richard Harang, Konrad Rieck, Rachel Greenstadt and Arvind Narayanan.
Proc. of the 25th Network and Distributed System Security Symposium (NDSS), February 2018.
Static Program Analysis as a Fuzzing Aid.
Bhargava Shastry, Markus Leutner, Tobias Fiebig, Kashyap Thimmaraju, Fabian Yamaguchi, Konrad Rieck, Stefan Schmid, Jean-Pierre Seifert and Anja Feldmann.
Proc. of the 20th Symposium on Research in Attacks, Intrusions, and Defenses (RAID), September 2017.
Static Exploration of Taint-Style Vulnerabilities Found by Fuzzing.
Bhargava Shastry, Federico Maggi, Fabian Yamaguchi, Konrad Rieck and Jean-Pierre Seifert.
Proc. of the USENIX Workshop on Offensive Technologies (WOOT), August 2017.
Leveraging Flawed Tutorials for Seeding Large-Scale Web Vulnerability Discovery.
Tommi Unruh, Bhargava Shastry, Malte Skoruppa, Federico Maggi, Konrad Rieck, Jean-Pierre Seifert and Fabian Yamaguchi.
Proc. of the USENIX Workshop on Offensive Technologies (WOOT), August 2017.
Yes, Machine Learning Can Be More Secure! A Case Study on Android Malware Detection.
Ambra Demontis, Marco Melis, Battista Biggio, Davide Maiorca, Daniel Arp, Konrad Rieck, Igino Corona, Giorgio Giacinto and Fabio Roli.
IEEE Transactions on Dependable and Secure Computing (TDSC), May 2017.
Special Issue on Vulnerability Analysis.
Konrad Rieck.
Information Technology (IT), 59 (2), 57–58, De Gruyter, April 2017.
64-bit Migration Vulnerabilities.
Christian Wressnegger, Fabian Yamaguchi, Alwin Maier and Konrad Rieck.
Information Technology (IT), 59 (2), 73–82, De Gruyter, April 2017.
Privacy Threats through Ultrasonic Side Channels on Mobile Devices.
Daniel Arp, Erwin Quiring, Christian Wressnegger and Konrad Rieck.
Proc. of the 2nd IEEE European Symposium on Security and Privacy (EuroS&P), 35–47, April 2017.
Efficient and Flexible Discovery of PHP Application Vulnerabilities.
Michael Backes, Konrad Rieck, Malte Skoruppa, Ben Stock and Fabian Yamaguchi.
Proc. of the 2nd IEEE European Symposium on Security and Privacy (EuroS&P), April 2017.
TrustJS: Trusted Client-side Execution of JavaScript.
David Goltzsche, Colin Wulf, Divya Muthukumaran, Konrad Rieck, Peter Pietzuch and Rüdiger Kapitza.
Proc. of the 10th ACM European Workshop on Systems Security (EuroSec), April 2017.
Looking Back on Three Years of Flash-based Malware.
Christian Wressnegger and Konrad Rieck.
Proc. of the 10th ACM European Workshop on Systems Security (EuroSec), April 2017.
Automatically Inferring Malware Signatures for Anti-Virus Assisted Attacks.
Christian Wressnegger, Kevin Freeman, Fabian Yamaguchi and Konrad Rieck.
Proc. of the ACM Asia Conference on Computer and Communications Security (ASIACCS), 587–598, April 2017.
Mining Attributed Graphs for Threat Intelligence.
Hugo Gascon, Bernd Grobauer, Thomas Schreck, Lukas Rist, Daniel Arp and Konrad Rieck.
Proc. of the 8th ACM Conference on Data and Applications Security and Privacy (CODASPY), 15–22, March 2017.
Fraternal Twins: Unifying Attacks on Machine Learning and Digital Watermarking.
Erwin Quiring, Daniel Arp and Konrad Rieck.
Technical report, arXiv:1703.05561, March 2017.
Multi-objective Ant Colony Optimisation in Wireless Sensor Networks.
Ansgar Kellner.
Nature-Inspired Computing and Optimization, 51–78, Springer, 2017.
Twice the Bits, Twice the Trouble: Vulnerabilities Induced by Migrating to 64-Bit Platforms.
Christian Wressnegger, Fabian Yamaguchi, Alwin Maier and Konrad Rieck.
Proc. of the 23rd ACM Conference on Computer and Communications Security (CCS), 541–552, October 2016.
From Malware Signatures to Anti-Virus Assisted Attacks.
Christian Wressnegger, Kevin Freeman, Fabian Yamaguchi and Konrad Rieck.
Technical report, Technische Universität Braunschweig, (2016-03), October 2016.
Die Codeanalyseplattform “Octopus”.
Fabian Yamaguchi and Konrad Rieck.
Datenschutz und Datensicherheit (DuD), 40 (11), 713–717, October 2016.
Bat in the Mobile: A Study on Ultrasonic Device Tracking.
Daniel Arp, Erwin Quiring, Christian Wressnegger and Konrad Rieck.
Technical report, Technische Universität Braunschweig, (2016-02), September 2016.
Towards Vulnerability Discovery Using Staged Program Analysis.
Bhargava Shastry, Fabian Yamaguchi, Konrad Rieck and Jean-Pierre Seifert.
Proc. of the 13th Conference on Detection of Intrusions and Malware & Vulnerability Assessment (DIMVA), 78–97, July 2016.
Comprehensive Analysis and Detection of Flash-based Malware.
Christian Wressnegger, Fabian Yamaguchi, Daniel Arp and Konrad Rieck.
Proc. of the 13th Conference on Detection of Intrusions and Malware & Vulnerability Assessment (DIMVA), 101–121, July 2016.
Best Paper Award
Monte Carlo Localization for Path-Based Mobility in Mobile Wireless Sensor Networks.
Salke Hartung, Ansgar Kellner, Konrad Rieck and Dieter Hogrefe.
Proc. of the 18th IEEE Wireless Communications and Networking Conference (WCNC), 1–7, April 2016.
Harry: A Tool for Measuring String Similarity.
Konrad Rieck and Christian Wressnegger.
Journal of Machine Learning Research (JMLR), 17 (9), 1–5, March 2016.
When Coding Style Survives Compilation: De-anonymizing Programmers from Executable Binaries.
Aylin Caliskan, Fabian Yamaguchi, Edwin Dauber, Richard Harang, Konrad Rieck, Rachel Greenstadt and Arvind Narayanan.
Technical report, Computing Research Repository, (abs/1512.08546), December 2015.
Analyzing and Detecting Flash-based Malware using Lightweight Multi-Path Exploration.
Christian Wressnegger, Fabian Yamaguchi, Daniel Arp and Konrad Rieck.
Technical report, University of Göttingen, (IFI-TB-2015-05), December 2015.
Pulsar: Stateful Black-Box Fuzzing of Proprietary Network Protocols.
Hugo Gascon, Christian Wressnegger, Fabian Yamaguchi, Daniel Arp and Konrad Rieck.
Proc. of the 11th International Conference on Security and Privacy in Communication Networks (SECURECOMM), 330–347, October 2015.
VCCFinder: Finding Potential Vulnerabilities in Open-Source Projects to Assist Code Audits.
Henning Perl, Daniel Arp, Sergej Dechand, Sascha Fahl, Yasemin Acar, Fabian Yamaguchi, Konrad Rieck and Matthew Smith.
Proc. of the 22nd ACM Conference on Computer and Communications Security (CCS), October 2015.
Fingerprinting Mobile Devices Using Personalized Configurations.
Andreas Kurtz, Hugo Gascon, Tobias Becker, Konrad Rieck and Felix Freiling.
Proceedings on Privacy Enhancing Technologies (PETS), 2016 (1), 4–19, September 2015.
De-anonymizing Programmers via Code Stylometry.
Aylin Caliskan-Islam, Richard Harang, Andrew Liu, Arvind Narayanan, Clare Voss, Fabian Yamaguchi and Rachel Greenstadt.
Proc. of the 24th USENIX Security Symposium, 255–270, August 2015.
Automatic Inference of Search Patterns for Taint-Style Vulnerabilities.
Fabian Yamaguchi, Alwin Maier, Hugo Gascon and Konrad Rieck.
Proc. of the 36th IEEE Symposium on Security and Privacy (S&P), May 2015.
Torben: A Practical Side-Channel Attack for Deanonymizing Tor Communication.
Daniel Arp, Fabian Yamaguchi and Konrad Rieck.
Proc. of the 10th ACM Symposium on Information, Computer and Communications Security (ASIACCS), April 2015.
Torben: Deanonymizing Tor Communication using Web Page Markers.
Daniel Arp, Fabian Yamaguchi and Konrad Rieck.
Technical report, University of Göttingen, (IFI-TB-2014-01), December 2014.
Poisoning Behavioral Malware Clustering.
Battista Biggio, Konrad Rieck, Davide Ariu, Christian Wressnegger, Igino Corona, Giorgio Giacinto and Fabio Roli.
Proc. of the 7th ACM Workshop on Artificial Intelligence and Security (AISEC), 1–10, November 2014.
Special Issue on Threat Detection, Analysis and Defense.
Shujun Li, Konrad Rieck and Alan Woodward.
Journal of Information Security and Applications (JISA), 19 (3), 163–164, July 2014.
Mobile-Sandbox: Combining Static and Dynamic Analysis with Machine Learning Techniques.
Michael Spreitzenbarth, Thomas Schreck, Florian Echtler, Daniel Arp and Johannes Hoffmann.
International Journal of Information Security, 1–13, Springer, July 2014.
Modeling and Discovering Vulnerabilities with Code Property Graphs.
Fabian Yamaguchi, Nico Golde, Daniel Arp and Konrad Rieck.
Proc. of the 35th IEEE Symposium on Security and Privacy (S&P), May 2014.
Continuous Authentication on Mobile Devices by Analysis of Typing Motion Behavior.
Hugo Gascon, Sebastian Uellenbeck, Christopher Wolf and Konrad Rieck.
Proc. of the GI Conference “Sicherheit, Schutz und Zuverlässigkeit” (SICHERHEIT), March 2014.
Drebin: Efficient and Explainable Detection of Android Malware in Your Pocket.
Daniel Arp, Michael Spreitzenbarth, Malte Hübner, Hugo Gascon and Konrad Rieck.
Proc. of the 21st Network and Distributed System Security Symposium (NDSS), February 2014.
Structural Detection of Android Malware using Embedded Call Graphs.
Hugo Gascon, Fabian Yamaguchi, Daniel Arp and Konrad Rieck.
Proc. of the 6th ACM Workshop on Artificial Intelligence and Security (AISEC), 45–54, November 2013.
Off the Beaten Path: Machine Learning for Offensive Security.
Konrad Rieck.
Proc. of the 6th ACM Workshop on Artificial Intelligence and Security (AISEC), 1–2, (Keynote) November 2013.
A Close Look on n-Grams in Intrusion Detection: Anomaly Detection vs. Classification.
Christian Wressnegger, Guido Schwenk, Daniel Arp and Konrad Rieck.
Proc. of the 6th ACM Workshop on Artificial Intelligence and Security (AISEC), 67–76, November 2013.
Chucky: Exposing Missing Checks in Source Code for Vulnerability Discovery.
Fabian Yamaguchi, Christian Wressnegger, Hugo Gascon, Charles Ray and Konrad Rieck.
Proc. of the 20th ACM Conference on Computer and Communications Security (CCS), 499–510, November 2013.
Deobfuscating Embedded Malware using Probable-Plaintext Attacks.
Christian Wressnegger, Frank Boldewin and Konrad Rieck.
Proc. of the 16th Symposium on Research in Attacks, Intrusions, and Defenses (RAID), 164–183, October 2013.
Drebin: Efficient and Explainable Detection of Android Malware in Your Pocket.
Daniel Arp, Michael Spreitzenbarth, Malte Hübner, Hugo Gascon and Konrad Rieck.
Technical report, University of Göttingen, (IFI-TB-2013-02), August 2013.
Proceedings of 10th Conference on Detection of Intrusions and Malware & Vulnerability Assessment.
Konrad Rieck, Patrick Stewin and Jean-Pierre Seifert (Eds.)
Springer, July 2013.
Toward Supervised Anomaly Detection.
Nico Görnitz, Marius Kloft, Konrad Rieck and Ulf Brefeld.
Journal of Artificial Intelligence Research (JAIR), 46 (1), 235–262, February 2013.
Generalized Vulnerability Extrapolation using Abstract Syntax Trees.
Fabian Yamaguchi, Markus Lottmann and Konrad Rieck.
Proc. of the 28th Annual Computer Security Applications Conference (ACSAC), 359–368, December 2012.
Outstanding Paper Award
Sally: A Tool for Embedding Strings in Vector Spaces.
Konrad Rieck, Christian Wressnegger and Alexander Bikadorov.
Journal of Machine Learning Research (JMLR), 13 (Nov), 3247–3251, November 2012.
Learning Stateful Models for Network Honeypots.
Tammo Krueger, Hugo Gascon, Nicole Kraemer and Konrad Rieck.
Proc. of the 5th ACM Workshop on Artificial Intelligence and Security (AISEC), 37–48, October 2012.
Early Detection of Malicious Behavior in JavaScript Code.
Kristof Schütt, Alexander Bikadorov, Marius Kloft and Konrad Rieck.
Proc. of the 5th ACM Workshop on Artificial Intelligence and Security (AISEC), 15–24, October 2012.
Autonomous Learning for Detection of JavaScript Attacks: Vision or Reality?.
Guido Schwenk, Alexander Bikadorov, Tammo Krueger and Konrad Rieck.
Proc. of the 5th ACM Workshop on Artificial Intelligence and Security (AISEC), 93–104, October 2012.
Intelligent Defense against Malicious JavaScript Code.
Tammo Krueger and Konrad Rieck.
Praxis der Informationsverarbeitung und Kommunikation (PIK), 35 (1), 54–60, April 2012.
Support Vector Machines.
Konrad Rieck, Sören Sonnenburg, Sebastian Mika, Christian Schäfer, Pavel Laskov, David Tax and Klaus-Robert Müller.
Handbook of Computational Statistics, Second edition, 883–926, Springer, 2012.
Smart Metering De-Pseudonymization.
Marek Jawurek, Martin Johns and Konrad Rieck.
Proc. of the 27th Annual Computer Security Applications Conference (ACSAC), 227–236, December 2011.
Adaptive Detection of Covert Communication in HTTP Requests.
Guido Schwenk and Konrad Rieck.
Proc. of the 7th European Conference on Network Defense (EC2ND), 25 — 32, September 2011.
Vulnerability Extrapolation: Assisted Discovery of Vulnerabilities using Machine Learning.
Fabian Yamaguchi, Felix Lindner and Konrad Rieck.
Proc. of the USENIX Workshop on Offensive Technologies (WOOT), 118–127, August 2011.
Similarity Measures for Sequential Data.
Konrad Rieck.
WIREs: Data Mining and Knowledge Discovery, 1 (4), 296–304, Wiley, July 2011.
Computer Security and Machine Learning: Worst Enemies or Best Friends?.
Konrad Rieck.
Proc. of the 1st Workshop on Systems Security (SYSSEC), 107 — 110, July 2011.
Automatic Analysis of Malware Behavior using Machine Learning.
Konrad Rieck, Philipp Trinius, Carsten Willems and Thorsten Holz.
Journal of Computer Security (JCS), 19 (4), 639–668, IOSPress, June 2011.
Self-Learning Network Intrusion Detection.
Konrad Rieck.
Information Technology (IT), 53 (3), 152–156, Oldenbourg, May 2011.
Analysis of Update Delays in Signature-based Network Intrusion Detection Systems.
Hugo Gascon, Agustin Orfila and Jorge Alis.
Computers & Security, 30 (8), 613–624, 2011.
Cujo: Efficient Detection and Prevention of Drive-by-Download Attacks.
Konrad Rieck, Tammo Krueger and Andreas Dewald.
Proc. of the 26th Annual Computer Security Applications Conference (ACSAC), 31–39, December 2010.
Proceedings of 6th European Conference on Computer Network Defense.
Konrad Rieck (Ed.)
IEEE Computer Society, November 2010.
A Malware Instruction Set for Behavior-based Analysis.
Philipp Trinius, Carsten Willems, Thorsten Holz and Konrad Rieck.
Proc. of the GI Conference “Sicherheit, Schutz und Zuverlässigkeit” (SICHERHEIT), 205–216, October 2010.
ASAP: Automatic Semantics-Aware Analysis of Network Payloads.
Tammo Krueger, Nicole Kraemer and Konrad Rieck.
Proc. of the ECML Workshop on Privacy and Security Issues in Machine Learning, 50–63, September 2010.
Cujo: Efficient Detection and Prevention of Drive-by-Download Attacks.
Konrad Rieck, Tammo Krueger and Andreas Dewald.
Technical report, Technische Universität Berlin, (2010-10), July 2010.
TokDoc: A Self-Healing Web Application Firewall.
Tammo Krueger, Christian Gehl, Konrad Rieck and Pavel Laskov.
Proc. of the 25th ACM Symposium on Applied Computing (SAC), 1846–1853, March 2010.
Botzilla: Detecting the “Phoning Home” of Malicious Software.
Konrad Rieck, Guido Schwenk, Tobias Limmer, Thorsten Holz and Pavel Laskov.
Proc. of the 25th ACM Symposium on Applied Computing (SAC), 1978–1984, March 2010.
Approximate Tree Kernels.
Konrad Rieck, Tammo Krueger, Ulf Brefeld and Klaus-Robert Müller.
Journal of Machine Learning Research (JMLR), 11 (Feb), 555–580, February 2010.
FIPS: FIRST Intrusion Prevention System.
Ingmar Schuster, Tammo Krueger, Christian Gehl, Konrad Rieck and Pavel Laskov.
Technical report, Fraunhofer Institute FIRST, (FIRST 1/2010), February 2010.
Automatic Analysis of Malware Behavior using Machine Learning.
Konrad Rieck, Philipp Trinius, Carsten Willems and Thorsten Holz.
Technical report, Technische Universität Berlin, (2009-18), December 2009.
A Malware Instruction Set for Behavior-Based Analysis.
Philipp Trinius, Carsten Willems, Thorsten Holz and Konrad Rieck3.
Technical report, University of Mannheim, (TR-2009-07), December 2009.
Active Learning for Network Intrusion Detection.
Nico Görnitz, Marius Kloft, Konrad Rieck and Ulf Brefeld.
Proc. of the 2nd ACM Workshop on Artificial Intelligence and Security (AISEC), 47–54, November 2009.
Visualization and Explanation of Payload-Based Anomaly Detection.
Konrad Rieck and Pavel Laskov.
Proc. of the 5th European Conference on Network Defense (EC2ND), November 2009.
Securing IMS against Novel Threats.
Stefan Wahl, Konrad Rieck, Pavel Laskov, Peter Domschitz and Klaus-Robert Müller.
Bell Labs Technical Journal, 14 (1), 243–257, Wiley, May 2009.
Incorporation of Application Layer Protocol Syntax into Anomaly Detection.
Patrick Düssel, Christian Gehl, Pavel Laskov and Konrad Rieck..
Proc. of the 4th International Conference on Information Systems Security (ICISS), 188–202, December 2008.
An Architecture for Inline Anomaly Detection.
Tammo Krueger, Christian Gehl, Konrad Rieck and Pavel Laskov.
Proc. of the 4th European Conference on Network Defense (EC2ND), 11–18, December 2008.
Machine Learning for Intrusion Detection.
Pavel Laskov, Konrad Rieck and Klaus-Robert Müller.
Mining Massive Data Sets for Security, 366–373, IOS press, September 2008.
Approximate Kernels for Trees.
Konrad Rieck, Ulf Brefeld and Tammo Krueger.
Technical report, Fraunhofer Institute FIRST, (FIRST 5/2008), September 2008.
Learning and Classification of Malware Behavior.
Konrad Rieck, Thorsten Holz, Carsten Willems, Patrick Düssel and Pavel Laskov.
Proc. of the 5th Conference on Detection of Intrusions and Malware & Vulnerability Assessment (DIMVA), 108–125, July 2008.
A Self-Learning System for Detection of Anomalous SIP Messages.
Konrad Rieck, Stefan Wahl, Pavel Laskov, Peter Domschitz and Klaus-Robert Müller.
Principles, Systems and Applications of IP Telecommunications (IPTCOMM), 90–106, July 2008.
Requirements for Network Monitoring from an IDS Perspective.
Lothar Braun, Falko Dressler, Thorsten Holz, Engin Kirda, Jan Kohlrausch, Christopher Kruegel, Tobias Limmer, Konrad Rieck and James Sterbenz.
Perspectives Workshop: Network Attack Detection and Defense (Dagstuhl Proceedings), March 2008.
Attack Taxonomy.
Marc Dacier, Herve Debar, Thorsten Holz, Engin Kirda, Jan Kohlrausch, Christopher Kruegel, Konrad Rieck and James Sterbenz.
Perspectives Workshop: Network Attack Detection and Defense (Dagstuhl Proceedings), March 2008.
Measuring and Detecting Fast-Flux Service Networks.
Thorsten Holz, Christian Gorecki, Konrad Rieck and Felix Freiling.
Proc. of the 15th Network and Distributed System Security Symposium (NDSS), February 2008.
Linear-Time Computation of Similarity Measures for Sequential Data.
Konrad Rieck and Pavel Laskov.
Journal of Machine Learning Research (JMLR), 9 (Jan), 23–48, Microtome, January 2008.
Computation of Similarity Measures for Sequential Data using Generalized Suffix Trees.
Konrad Rieck, Pavel Laskov and Sören Sonnenburg.
Advances in Neural Information Processing Systems (NIPS), December 2007.
Large scale learning with string kernels.
Sören Sonnenburg, Gunnar Rätsch and Konrad Rieck.
Large Scale Kernel Machines, 73–103, MIT Press, September 2007.
Language Models for Detection of Unknown Attacks in Network Traffic.
Konrad Rieck and Pavel Laskov.
Journal in Computer Virology (JICV), 2 (4), 243–256, Springer, January 2007.
Efficient Algorithms for Similarity Measures over Sequential Data: A Look beyond Kernels.
Konrad Rieck, Pavel Laskov and Klaus-Robert Müller.
Proc. of the DAGM Symposium on Pattern Recognition, 374–383, September 2006.
Detecting Unknown Network Attacks using Language Models.
Konrad Rieck and Pavel Laskov.
Proc. of the 3rd Conference on Detection of Intrusions and Malware & Vulnerability Assessment (DIMVA), 74–90, July 2006.
Learning intrusion detection: supervised or unsupervised?.
Pavel Laskov, Patrick Düssel, Christin Schäfer and Konrad Rieck.
Proc. of the 13th International Conference on Image Analysis and Processing (ICIAP), 50–57, September 2005.
Visualization of anomaly detection using prediction sensitivity.
Pavel Laskov, Konrad Rieck, Christin Schäfer and Klaus-Robert Müller.
Proc. of the GI Conference “Sicherheit, Schutz und Zuverlässigkeit” (SICHERHEIT), 197–208, April 2005.