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Max Landauer
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2020 – today
- 2025
- [j16]Max Landauer, Florian Skopik, Branka Stojanovic, Andreas Flatscher, Torsten Ullrich:
A review of time-series analysis for cyber security analytics: from intrusion detection to attack prediction. Int. J. Inf. Sec. 24(1): 3 (2025) - 2024
- [j15]Markus Wurzenberger
, Georg Höld, Max Landauer
Analysis of statistical properties of variables in log data for advanced anomaly detection in cyber security. Comput. Secur. 137: 103631 (2024) - [j14]Manuel Kern
A logging maturity and decision model for the selection of intrusion detection cyber security solutions. Comput. Secur. 141: 103844 (2024) - [j13]Max Landauer
A Critical Review of Common Log Data Sets Used for Evaluation of Sequence-Based Anomaly Detection Techniques. Proc. ACM Softw. Eng. 1(FSE): 1354-1375 (2024) - [c15]Markus Wurzenberger
NEWSROOM: Towards Automating Cyber Situational Awareness Processes and Tools for Cyber Defence. ARES 2024: 69:1-69:11 - [c14]Florian Skopik
On the Application of Natural Language Processing for Advanced OSINT Analysis in Cyber Defence. ARES 2024: 71:1-71:10 - [c13]Max Landauer
Introducing a New Alert Data Set for Multi-Step Attack Analysis. CSET @ USENIX Security Symposium 2024: 41-53 - [i8]Max Landauer, Klaus Mayer, Florian Skopik, Markus Wurzenberger, Manuel Kern:
Red Team Redemption: A Structured Comparison of Open-Source Tools for Adversary Emulation. CoRR abs/2408.15645 (2024) - 2023
- [j12]Max Landauer, Markus Wurzenberger, Florian Skopik, Wolfgang Hotwagner, Georg Höld:
AMiner: A Modular Log Data Analysis Pipeline for Anomaly-based Intrusion Detection. DTRAP 4(1): 12:1-12:16 (2023) - [j11]Florian Skopik
Behavior-Based Anomaly Detection in Log Data of Physical Access Control Systems. IEEE Trans. Dependable Secur. Comput. 20(4): 3158-3175 (2023) - [j10]Max Landauer
Maintainable Log Datasets for Evaluation of Intrusion Detection Systems. IEEE Trans. Dependable Secur. Comput. 20(4): 3466-3482 (2023) - [c12]Patrick Himler
Towards Detecting Anomalies in Log-Event Sequences with Deep Learning: Open Research Challenges. EICC 2023: 71-77 - [i7]Max Landauer, Florian Skopik, Markus Wurzenberger:
Introducing a New Alert Data Set for Multi-Step Attack Analysis. CoRR abs/2308.12627 (2023) - [i6]Max Landauer, Florian Skopik, Markus Wurzenberger:
A Critical Review of Common Log Data Sets Used for Evaluation of Sequence-based Anomaly Detection Techniques. CoRR abs/2309.02854 (2023) - 2022
- [j9]Florian Skopik
Online Log Data Analysis With Efficient Machine Learning: A Review. IEEE Secur. Priv. 20(3): 80-90 (2022) - [j8]Florian Skopik
Blind Spots of Security Monitoring in Enterprise Infrastructures: A Survey. IEEE Secur. Priv. 20(6): 18-26 (2022) - [j7]Max Landauer
Dealing with Security Alert Flooding: Using Machine Learning for Domain-independent Alert Aggregation. ACM Trans. Priv. Secur. 25(3): 18:1-18:36 (2022) - [c11]Max Landauer
A User and Entity Behavior Analytics Log Data Set for Anomaly Detection in Cloud Computing. IEEE Big Data 2022: 4285-4294 - [c10]Max Landauer
A Framework for Automatic Labeling of Log Datasets from Model-driven Testbeds for HIDS Evaluation. SAT-CPS@CODASPY 2022: 77-86 - [c9]Manuel Kern, Florian Skopik, Max Landauer, Edgar R. Weippl:
Strategic selection of data sources for cyber attack detection in enterprise networks: a survey and approach. SAC 2022: 1656-1665 - [p2]Florian Skopik
Detecting Unknown Cyber Security Attacks Through System Behavior Analysis. Cybersecurity of Digital Service Chains 2022: 103-119 - [p1]Markus Wurzenberger
Automatic Attack Pattern Mining for Generating Actionable CTI Applying Alert Aggregation. Cybersecurity of Digital Service Chains 2022: 136-161 - [i5]Max Landauer, Florian Skopik, Maximilian Frank, Wolfgang Hotwagner, Markus Wurzenberger, Andreas Rauber:
Maintainable Log Datasets for Evaluation of Intrusion Detection Systems. CoRR abs/2203.08580 (2022) - [i4]Max Landauer, Sebastian Onder, Florian Skopik, Markus Wurzenberger:
Deep Learning for Anomaly Detection in Log Data: A Survey. CoRR abs/2207.03820 (2022) - [i3]Max Landauer, Florian Skopik, Markus Wurzenberger, Wolfgang Hotwagner:
Kyoushi Testbed Environment: A Model-driven Simulation Framework to Generate Open Log Data Sets for Security Evaluations. ERCIM News 2022(129): 0 (2022) - 2021
- [b1]Florian Skopik
Smart Log Data Analytics - Techniques for Advanced Security Analysis. Springer 2021, ISBN 978-3-030-74449-6, pp. 1-208 - [j6]Florian Skopik
The Seven Golden Principles of Effective Anomaly-Based Intrusion Detection. IEEE Secur. Priv. 19(5): 36-45 (2021) - [j5]Maria Leitner
Enabling exercises, education and research with a comprehensive cyber range. J. Wirel. Mob. Networks Ubiquitous Comput. Dependable Appl. 12(4): 37-61 (2021) - [j4]Max Landauer
Have it Your Way: Generating Customized Log Datasets With a Model-Driven Simulation Testbed. IEEE Trans. Reliab. 70(1): 402-415 (2021) - [c8]Max Landauer, Georg Höld, Markus Wurzenberger, Florian Skopik, Andreas Rauber:
Iterative Selection of Categorical Variables for Log Data Anomaly Detection. ESORICS (1) 2021: 757-777 - 2020
- [j3]Max Landauer
System log clustering approaches for cyber security applications: A survey. Comput. Secur. 92: 101739 (2020) - [j2]Florian Skopik
synERGY: Cross-correlation of operational and contextual data to timely detect and mitigate attacks to cyber-physical systems. J. Inf. Secur. Appl. 54: 102544 (2020) - [c7]Markus Wurzenberger
Creating Character-based Templates for Log Data to Enable Security Event Classification. AsiaCCS 2020: 141-152 - [c6]Max Landauer, Florian Skopik, Markus Wurzenberger, Wolfgang Hotwagner, Andreas Rauber:
Visualizing Syscalls using Self-organizing Maps for System Intrusion Detection. ICISSP 2020: 349-360 - [c5]Max Landauer, Florian Skopik, Markus Wurzenberger, Wolfgang Hotwagner, Andreas Rauber:
Have It Your Way: Generating Customized Log Data Sets with a Model-driven Simulation Testbed. QRS 2020: 52 - [i2]Florian Skopik, Markus Wurzenberger, Max Landauer:
DECEPT: Detecting Cyber-Physical Attacks using Machine Learning on Log Data. ERCIM News 2020(123) (2020)
2010 – 2019
- 2019
- [c4]Max Landauer, Florian Skopik, Markus Wurzenberger, Wolfgang Hotwagner, Andreas Rauber:
A Framework for Cyber Threat Intelligence Extraction from Raw Log Data. IEEE BigData 2019: 3200-3209 - [c3]Markus Wurzenberger, Max Landauer, Florian Skopik, Wolfgang Kastner:
AECID-PG: A Tree-Based Log Parser Generator To Enable Log Analysis. IM 2019: 7-12 - [i1]Max Landauer, Florian Skopik:
INDICÆTING - Automatically Detecting, Extracting, and Correlating Cyber Threat Intelligence from Raw Computer Log Data. ERCIM News 2019(116) (2019) - 2018
- [j1]Max Landauer, Markus Wurzenberger, Florian Skopik
Dynamic log file analysis: An unsupervised cluster evolution approach for anomaly detection. Comput. Secur. 79: 94-116 (2018) - [c2]Max Landauer, Markus Wurzenberger, Florian Skopik, Giuseppe Settanni, Peter Filzmoser
Time Series Analysis: Unsupervised Anomaly Detection Beyond Outlier Detection. ISPEC 2018: 19-36 - 2017
- [c1]Markus Wurzenberger, Florian Skopik, Max Landauer, Philipp Greitbauer, Roman Fiedler, Wolfgang Kastner
Incremental Clustering for Semi-Supervised Anomaly Detection applied on Log Data. ARES 2017: 31:1-31:6
Coauthor Index
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