IT Security + Data Science + Big Data

Contact

  • grimmer [at] informatik.uni-leipzig.de

  • Leipzig University, Ritterstraße 12, 04109 Leipzig, Germany

  • Room 207

About Me

  • Since 09/2020: ZIM-Project „Angriffsbasierte Automatisierung von Security Testing für IoT-Anwendungen“
    (Attack-based automation of security testing for IoT applications)

  • Since 08/2016: PhD student / research assistant, Leipzig University, database group in the EXPLOIDS project

  • 03/2014 - 07/2016: IT-Specialist, mgm technology partners GmbH

    • BigData projects in the automotive and e-commerce sector

  • 08/2012 - 02/2014: Algorithm Engineer at Unister GmbH, R&D

    • BigData algorithmics for a semantic search engine

  • M.Sc. Computer Science, MLU Halle-Wittenberg, 03/2013

Current Topics

  • Host and Anomaly based Intrusion Detection Systems

  • Leipzig Intrusion Detection Data Set (LID-DS)

  • Security & Big Data

    • Intrusion Detection Systems, Anomaly Detection, Machine Learning

    • Distributed Computation Frameworks (Flink, Spark, etc.) and Storage Systems (Accumulo, HBase, etc.)

Talks, blog posts and more

Paper

  • Martin Max Röhling; Martin Grimmer; Dennis Kreußel; Jörn Hoffmann; Bogdan Franczyk, Standardized container virtualization approach for collecting host intrusion detection data, FedCSIS, 2019 [link]

  • Martin Grimmer; Martin Max Röhling; Dennis Kreusel; Simon Ganz, A Modern and Sophisticated Host Based Intrusion Detection Data Set, 16. Deutscher IT-Sicherheitskongress, 2019 [pdf]

  • Martin Grimmer; Martin Max Röhling; Matthias Kricke; Bogdan Franczyk; Erhard Rahm, Intrusion Detection on System Call Graphs, 25. DFN-Konferenz “Sicherheit in vernetzten Systemen”, 2018 [pdf]

  • Matthias Kricke; Martin Grimmer; Michael Schmeißer, Preserving Recomputability of Results from Big Data Transformation Workflows Depending on External Systems and Human Interaction, Datenbank-Spektrum, 2017-09 [link]

  • Pascal Hirmer; Tim Waizenegger; Ghareeb Falazi; Majd Abdo; Yuliya Volga; Alexander Askinadze; Matthias Liebeck; Stefan Conrad; Tobias Hildebrandt; Conrad Indiono; Stefanie Rinderle-Ma; Martin Grimmer; Matthias Kricke; Eric Peukert, The First Data Science Challenge at BTW 2017, Datenbank-Spektrum, 2017-09 [link]

  • Matthias Kricke; Martin Grimmer; Michael Schmeißer, Preserving Recomputability of Results from Big Data Transformation Workflows, Workshop Proceedings BTW, Lecture Notes in Informatics(LNI), GI 2017, 2017-03 [pdf]

  • Annabell Berger; Martin Grimmer; Mathias Müller-Hannemann, Fully dynamic speed-up techniques for multi-criteria shortest path searches in time-dependent networks, International Symposium on Experimental Algorithms, Springer, Berlin, Heidelberg, 2010 [pdf]

Supervision of theses

  • MA Tim Kaelble: VAE-MAD-GAN for HIDS (2020)

  • BA Daniel Helmrich: Prototype a Practical Anomaly-Based NIDS Using Deep Learning Techniques. (2020)

  • BA Toni Rucks: Erweiterung und Verbesserung des LID-DS. (2020)

  • BA Greta Staskewitsch: Anomaly Detection basierend auf Sequenz- und Parameteranalysen von Systemcalls. (2020)

  • MA Dennis Kreußel: Stealth Attacks (working title) (2020)

  • MA Caroline Mösler: Deep Learning Konzepte eines Hosted-Based Intrusion Detection Systems auf dem LID-DS. (2020)

  • BA Dennis Kreußel: Simulation and analysis of system call traces for adversial anomaly detection. (2019)

  • MA Simon Ganz: Ein moderner Host Intrusion Detection Datensatz. (2019)

  • MA Lukas Werner: Verteilte exakte Berechnung von Perzentilen für Fließkommazahlen. (2018)

  • MA Marcel Jacob: Effiziente Haltung und Abfrage geotemporaler Daten im Apache Hadoop Ökosystem. (2015)