Incremental Clustering for Semi-Supervised Anomaly Detection applied on Log Data. - Markus Wurzenberger; Florian Skopik; Max Landauer; Philipp Greitbauer; Roman Fiedler; Wolfgang Kastner (ARES, 2017)

Time Series Analysis: Unsupervised Anomaly Detection Beyond Outlier Detection. - Max Landauer; Markus Wurzenberger; Florian Skopik; Giuseppe Settanni; Peter Filzmoser (ISPEC, 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)

A Framework for Cyber Threat Intelligence Extraction from Raw Log Data. - Max Landauer; Florian Skopik; Markus Wurzenberger; Wolfgang Hotwagner; Andreas Rauber (IEEE BigData, 2019)

AECID-PG: A Tree-Based Log Parser Generator To Enable Log Analysis. - Markus Wurzenberger; Max Landauer; Florian Skopik; Wolfgang Kastner (IM, 2019)

INDICÆTING - Automatically Detecting, Extracting, and Correlating Cyber Threat Intelligence from Raw Computer Log Data. - Max Landauer; Florian Skopik (ERCIM News, 2019)

Creating Character-based Templates for Log Data to Enable Security Event Classification. - Markus Wurzenberger; Georg Höld; Max Landauer; Florian Skopik; Wolfgang Kastner (AsiaCCS, 2020)

Visualizing Syscalls using Self-organizing Maps for System Intrusion Detection. - Max Landauer; Florian Skopik; Markus Wurzenberger; Wolfgang Hotwagner; Andreas Rauber (ICISSP, 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 (QRS, 2020)

System log clustering approaches for cyber security applications: A survey. - Max Landauer; Florian Skopik; Markus Wurzenberger; Andreas Rauber (Comput. Secur., 2020)

DECEPT: Detecting Cyber-Physical Attacks using Machine Learning on Log Data. - Florian Skopik; Markus Wurzenberger; Max Landauer (ERCIM News, 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; et al. (J. Inf. Secur. Appl., 2020)

Smart Log Data Analytics - Techniques for Advanced Security Analysis - Florian Skopik; Markus Wurzenberger; Max Landauer (Springer, 2021)

Iterative Selection of Categorical Variables for Log Data Anomaly Detection. - Max Landauer; Georg Höld; Markus Wurzenberger; Florian Skopik; Andreas Rauber (ESORICS (1), 2021)

The Seven Golden Principles of Effective Anomaly-Based Intrusion Detection. - Florian Skopik; Markus Wurzenberger; Max Landauer (IEEE Secur. Priv., 2021)

Enabling exercises, education and research with a comprehensive cyber range. - Maria Leitner; Maximilian Frank; Gregor Langner; Max Landauer; Florian Skopik; Paul Smith 001; Benjamin Akhras; Wolfgang Hotwagner; Stela Kucek; Timea Pahi; Lenhard Reuter; Manuel Warum (J. Wirel. Mob. Networks Ubiquitous Comput. Dependable Appl., 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)

A User and Entity Behavior Analytics Log Data Set for Anomaly Detection in Cloud Computing. - Max Landauer; Florian Skopik; Georg Höld; Markus Wurzenberger (IEEE Big Data, 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 (SAT-CPS@CODASPY, 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 (SAC, 2022)

Deep Learning for Anomaly Detection in Log Data: A Survey. - Max Landauer; Sebastian Onder; Florian Skopik; Markus Wurzenberger (CoRR, 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)

Online Log Data Analysis With Efficient Machine Learning: A Review. - Florian Skopik; Max Landauer; Markus Wurzenberger (IEEE Secur. Priv., 2022)

Blind Spots of Security Monitoring in Enterprise Infrastructures: A Survey. - Florian Skopik; Max Landauer; Markus Wurzenberger (IEEE Secur. Priv., 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)

Detecting Unknown Cyber Security Attacks Through System Behavior Analysis. - Florian Skopik; Markus Wurzenberger; Max Landauer (Cybersecurity of Digital Service Chains, 2022)

Automatic Attack Pattern Mining for Generating Actionable CTI Applying Alert Aggregation. - Markus Wurzenberger; Max Landauer; Agron Bajraktari; Florian Skopik (Cybersecurity of Digital Service Chains, 2022)

Towards Detecting Anomalies in Log-Event Sequences with Deep Learning: Open Research Challenges. - Patrick Himler; Max Landauer; Florian Skopik; Markus Wurzenberger (EICC, 2023)

AMiner: A Modular Log Data Analysis Pipeline for Anomaly-based Intrusion Detection. - Max Landauer; Markus Wurzenberger; Florian Skopik; Wolfgang Hotwagner; Georg Höld (DTRAP, 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)

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)

On the Application of Natural Language Processing for Advanced OSINT Analysis in Cyber Defence. - Florian Skopik; Benjamin Akhras; Elisabeth Woisetschläger; Medina Andresel; Markus Wurzenberger; Max Landauer (ARES, 2024)

NEWSROOM: Towards Automating Cyber Situational Awareness Processes and Tools for Cyber Defence. - Markus Wurzenberger; Stephan Krenn; Max Landauer; Florian Skopik; Cora Lisa Perner; Jarno Lötjönen; Jani Päijänen; Georgios Gardikis; Nikos Alabasis; Liisa Sakerman; Kristiina Omri; Juha Röning; et al. (ARES, 2024)

Semi-supervised Configuration and Optimization of Anomaly Detection Algorithms on Log Data. - Viktor Beck; Max Landauer; Markus Wurzenberger; Florian Skopik; Andreas Rauber (IEEE Big Data, 2024)

Evaluation and Comparison of Open-Source LLMs Using Natural Language Generation Quality Metrics. - Dzenan Hamzic; Markus Wurzenberger; Florian Skopik; Max Landauer; Andreas Rauber (IEEE Big Data, 2024)

Red Team Redemption: A Structured Comparison of Open-Source Tools for Adversary Emulation. - Max Landauer; Klaus Mayer; Florian Skopik; Markus Wurzenberger; Manuel Kern (TrustCom, 2024)

Introducing a New Alert Data Set for Multi-Step Attack Analysis. - Max Landauer; Florian Skopik; Markus Wurzenberger (CSET @ USENIX Security Symposium, 2024)

A logging maturity and decision model for the selection of intrusion detection cyber security solutions. - Manuel Kern; Max Landauer; Florian Skopik; Edgar R. Weippl (Comput. Secur., 2024)

A Critical Review of Common Log Data Sets Used for Evaluation of Sequence-Based Anomaly Detection Techniques. - Max Landauer; Florian Skopik; Markus Wurzenberger (Proc. ACM Softw. Eng., 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., 2024)

TTP Classification with Minimal Labeled Data: A Retrieval-Based Few-Shot Learning Approach. - Dzenan Hamzic; Florian Skopik; Max Landauer; Markus Wurzenberger; Andreas Rauber (ARES (2), 2025)

Enhancing Cyber Situational Awareness with AI: A Novel Pipeline Approach for Threat Intelligence Analysis and Enrichment. - Dzenan Hamzic; Florian Skopik; Max Landauer; Markus Wurzenberger; Andreas Rauber (ARES (Workshops 2), 2025)

Benign User Activities that Trigger False Positives in Intrusion Detection Systems: An Expert Survey. - Max Landauer; Florian Skopik; Markus Wurzenberger; Teodor Sommestad; Henrik Karlzén (ARES (Workshops 2), 2025)

SC4OSINT: A Story Clustering Approach to Optimize OSINT Analysis. - Elisabeth Woisetschläger; Medina Andresel; Florian Skopik; Benjamin Akhras; Peter Leitmann; Max Landauer; Markus Wurzenberger; Alexander Schindler (ARES (Workshops 2), 2025)

Towards Improving IDS Using CTF Events. - Manuel Kern; Florian Skopik; Max Landauer; Edgar R. Weippl (CoRR, 2025)

A review of time-series analysis for cyber security analytics: from intrusion detection to attack prediction. - Max Landauer; Florian Skopik; Branka Stojanovic; Andreas Flatscher; Torsten Ullrich (Int. J. Inf. Sec., 2025)

Trace of the Times: Rootkit Detection through Temporal Anomalies in Kernel Activity. - Max Landauer; Leonhard Alton; Martina Lindorfer; Florian Skopik; Markus Wurzenberger; Wolfgang Hotwagner (CoRR, 2025)

SoK: LLM-based Log Parsing. - Viktor Beck; Max Landauer; Markus Wurzenberger; Florian Skopik; Andreas Rauber (CoRR, 2025)

Identifying Open-Source Threat Detection Resources on GitHub: A Scalable Machine Learning Approach. - Manuel Kern; Max Landauer; Florian Skopik; Edgar R. Weippl (Int. J. Inf. Sec., 2025)