Max Landauer

According to our database, Max Landauer authored at least 33 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Analysis of statistical properties of variables in log data for advanced anomaly detection in cyber security.

Markus Wurzenberger, Georg Höld, Max Landauer, Florian Skopik

Comput. Secur., February, 2024

2023

Behavior-Based Anomaly Detection in Log Data of Physical Access Control Systems.

Florian Skopik, Markus Wurzenberger, Georg Höld, Max Landauer, Walter Kuhn

IEEE Trans. Dependable Secur. Comput., 2023

Maintainable Log Datasets for Evaluation of Intrusion Detection Systems.

Max Landauer, Florian Skopik, Maximilian Frank, Wolfgang Hotwagner, Markus Wurzenberger, Andreas Rauber

IEEE Trans. Dependable Secur. Comput., 2023

A Critical Review of Common Log Data Sets Used for Evaluation of Sequence-based Anomaly Detection Techniques.

Max Landauer, Florian Skopik, Markus Wurzenberger

CoRR, 2023

Introducing a New Alert Data Set for Multi-Step Attack Analysis.

Max Landauer, Florian Skopik, Markus Wurzenberger

CoRR, 2023

Towards Detecting Anomalies in Log-Event Sequences with Deep Learning: Open Research Challenges.

Patrick Himler, Max Landauer, Florian Skopik, Markus Wurzenberger

Proceedings of the 2023 European Interdisciplinary Cybersecurity Conference, 2023

2022

Automatic Attack Pattern Mining for Generating Actionable CTI Applying Alert Aggregation.

Markus Wurzenberger, Max Landauer, Agron Bajraktari, Florian Skopik

Proceedings of the Cybersecurity of Digital Service Chains, 2022

Detecting Unknown Cyber Security Attacks Through System Behavior Analysis.

Florian Skopik, Markus Wurzenberger, Max Landauer

Proceedings of the Cybersecurity of Digital Service Chains, 2022

Dealing with Security Alert Flooding: Using Machine Learning for Domain-independent Alert Aggregation.

Max Landauer, Florian Skopik, Markus Wurzenberger, Andreas Rauber

ACM Trans. Priv. Secur., 2022

Blind Spots of Security Monitoring in Enterprise Infrastructures: A Survey.

Florian Skopik, Max Landauer, Markus Wurzenberger

IEEE Secur. Priv., 2022

Online Log Data Analysis With Efficient Machine Learning: A Review.

Florian Skopik, Max Landauer, Markus Wurzenberger

IEEE Secur. Priv., 2022

Kyoushi Testbed Environment: A Model-driven Simulation Framework to Generate Open Log Data Sets for Security Evaluations.

Max Landauer, Florian Skopik, Markus Wurzenberger, Wolfgang Hotwagner

ERCIM News, 2022

Deep Learning for Anomaly Detection in Log Data: A Survey.

Max Landauer, Sebastian Onder, Florian Skopik, Markus Wurzenberger

CoRR, 2022

Strategic selection of data sources for cyber attack detection in enterprise networks: a survey and approach.

Manuel Kern, Florian Skopik, Max Landauer, Edgar R. Weippl

Proceedings of the SAC '22: The 37th ACM/SIGAPP Symposium on Applied Computing, Virtual Event, April 25, 2022

A Framework for Automatic Labeling of Log Datasets from Model-driven Testbeds for HIDS Evaluation.

Max Landauer, Maximilian Frank, Florian Skopik, Wolfgang Hotwagner, Markus Wurzenberger, Andreas Rauber

Proceedings of the Sat-CPS@CODASPY 2022: Proceedings of the 2022 ACM Workshop on Secure and Trustworthy Cyber-Physical Systems, 2022

A User and Entity Behavior Analytics Log Data Set for Anomaly Detection in Cloud Computing.

Max Landauer, Florian Skopik, Georg Höld, Markus Wurzenberger

Proceedings of the IEEE International Conference on Big Data, 2022

2021

Have it Your Way: Generating Customized Log Datasets With a Model-Driven Simulation Testbed.

Max Landauer, Florian Skopik, Markus Wurzenberger, Wolfgang Hotwagner, Andreas Rauber

IEEE Trans. Reliab., 2021

Enabling exercises, education and research with a comprehensive cyber range.

Maria Leitner, Maximilian Frank, Gregor Langner, Max Landauer, Florian Skopik, Paul Smith, Benjamin Akhras, Wolfgang Hotwagner, Stela Kucek, Timea Pahi, Lenhard Reuter, Manuel Warum

J. Wirel. Mob. Networks Ubiquitous Comput. Dependable Appl., 2021

The Seven Golden Principles of Effective Anomaly-Based Intrusion Detection.

Florian Skopik, Markus Wurzenberger, Max Landauer

IEEE Secur. Priv., 2021

Iterative Selection of Categorical Variables for Log Data Anomaly Detection.

Max Landauer, Georg Höld, Markus Wurzenberger, Florian Skopik, Andreas Rauber

Proceedings of the Computer Security - ESORICS 2021, 2021

Smart Log Data Analytics - Techniques for Advanced Security Analysis

Florian Skopik, Markus Wurzenberger, Max Landauer

Springer, ISBN: 978-3-030-74449-6, 2021

2020

synERGY: Cross-correlation of operational and contextual data to timely detect and mitigate attacks to cyber-physical systems.

Florian Skopik, Max Landauer, Markus Wurzenberger, Gernot Vormayr, Jelena Milosevic, Joachim Fabini, Wolfgang Prüggler, Oskar Kruschitz, Benjamin Widmann, Kevin Truckenthanner, Stefan Rass, Michael Simmer, Christoph Zauner

J. Inf. Secur. Appl., 2020

DECEPT: Detecting Cyber-Physical Attacks using Machine Learning on Log Data.

Florian Skopik, Markus Wurzenberger, Max Landauer

ERCIM News, 2020

System log clustering approaches for cyber security applications: A survey.

Max Landauer, Florian Skopik, Markus Wurzenberger, Andreas Rauber

Comput. Secur., 2020

Have It Your Way: Generating Customized Log Data Sets with a Model-driven Simulation Testbed.

Max Landauer, Florian Skopik, Markus Wurzenberger, Wolfgang Hotwagner, Andreas Rauber

Proceedings of the 20th IEEE International Conference on Software Quality, 2020

Visualizing Syscalls using Self-organizing Maps for System Intrusion Detection.

Max Landauer, Florian Skopik, Markus Wurzenberger, Wolfgang Hotwagner, Andreas Rauber

Proceedings of the 6th International Conference on Information Systems Security and Privacy, 2020

Creating Character-based Templates for Log Data to Enable Security Event Classification.

Markus Wurzenberger, Georg Höld, Max Landauer, Florian Skopik, Wolfgang Kastner

Proceedings of the ASIA CCS '20: The 15th ACM Asia Conference on Computer and Communications Security, 2020

2019

INDICÆTING - Automatically Detecting, Extracting, and Correlating Cyber Threat Intelligence from Raw Computer Log Data.

Max Landauer, Florian Skopik

ERCIM News, 2019

AECID-PG: A Tree-Based Log Parser Generator To Enable Log Analysis.

Markus Wurzenberger, Max Landauer, Florian Skopik, Wolfgang Kastner

Proceedings of the IFIP/IEEE International Symposium on Integrated Network Management, 2019

A Framework for Cyber Threat Intelligence Extraction from Raw Log Data.

Max Landauer, Florian Skopik, Markus Wurzenberger, Wolfgang Hotwagner, Andreas Rauber

Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

2018

Dynamic log file analysis: An unsupervised cluster evolution approach for anomaly detection.

Max Landauer, Markus Wurzenberger, Florian Skopik, Giuseppe Settanni, Peter Filzmoser

Comput. Secur., 2018

Time Series Analysis: Unsupervised Anomaly Detection Beyond Outlier Detection.

Max Landauer, Markus Wurzenberger, Florian Skopik, Giuseppe Settanni, Peter Filzmoser

Proceedings of the Information Security Practice and Experience, 2018

2017

Incremental Clustering for Semi-Supervised Anomaly Detection applied on Log Data.

Markus Wurzenberger, Florian Skopik, Max Landauer, Philipp Greitbauer, Roman Fiedler, Wolfgang Kastner

Proceedings of the 12th International Conference on Availability, Reliability and Security, Reggio Calabria, Italy, August 29, 2017