Markus Wurzenberger
TitelZitiert vonJahr
Incremental clustering for semi-supervised anomaly detection applied on log data
M Wurzenberger, F Skopik, M Landauer, P Greitbauer, R Fiedler, ...
Proceedings of the 12th International Conference on Availability …, 2017
102017
Correlating cyber incident information to establish situational awareness in Critical Infrastructures
G Settanni, Y Shovgenya, F Skopik, R Graf, M Wurzenberger, R Fiedler
Privacy, Security and Trust (PST), 2016 14th Annual Conference on, 78-81, 2016
102016
Establishing national cyber situational awareness through incident information clustering
F Skopik, M Wurzenberger, G Settanni, R Fiedler
2015 International Conference on Cyber Situational Awareness, Data Analytics …, 2015
102015
Dynamic log file analysis: An unsupervised cluster evolution approach for anomaly detection
M Landauer, M Wurzenberger, F Skopik, G Settanni, P Filzmoser
computers & security 79, 94-116, 2018
72018
Discovering insider threats from log data with high-performance bioinformatics tools
M Wurzenberger, F Skopik, R Fiedler, W Kastner
Proceedings of the 8th ACM CCS International Workshop on Managing Insider …, 2016
72016
Complex log file synthesis for rapid sandbox-benchmarking of security-and computer network analysis tools
M Wurzenberger, F Skopik, G Settanni, W Scherrer
Information Systems 60, 13-33, 2016
62016
Applying High-Performance Bioinformatics Tools for Outlier Detection in Log Data
M Wurzenberger, F Skopik, R Fiedler, W Kastner
Cybernetics (CYBCONF), 2017 3rd IEEE International Conference on, 1-10, 2017
52017
Acquiring Cyber Threat Intelligence through Security Information Correlation
G Settanni, Y Shovgenya, F Skopik, R Graf, M Wurzenberger, R Fiedler
Cybernetics (CYBCONF), 2017 3rd IEEE International Conference on, 1-7, 2017
52017
Time Series Analysis: Unsupervised Anomaly Detection Beyond Outlier Detection
M Landauer, M Wurzenberger, F Skopik, G Settanni, P Filzmoser
International Conference on Information Security Practice and Experience, 19-36, 2018
42018
Protecting cyber physical production systems using anomaly detection to enable self-adaptation
G Settanni, F Skopik, A Karaj, M Wurzenberger, R Fiedler
2018 IEEE Industrial Cyber-Physical Systems (ICPS), 173-180, 2018
42018
Towards a Resilience Metric Framework for Cyber-Physical Systems.
I Friedberg, K McLaughlin, P Smith, M Wurzenberger
ICS-CSR, 2016
42016
AECID: A Self-learning Anomaly Detection Approach Based on Light-weight Log Parser Models
M Wurzenberger, F Skopik, G Settanni, R Fiedler
4th International Conference on Information Systems Security and Privacy …, 2018
32018
AECID-PG: A Tree-Based Log Parser Generator To Enable Log Analysis
M Wurzenberger, M Landauer, F Skopik, W Kastner
2019 IFIP/IEEE Symposium on Integrated Network and Service Management (IM), 7-12, 2019
12019
synERGY: Detecting Advanced Attacks Across Multiple Layers of Cyber-Physical Systems
F Skopik, M Wurzenberger, R Fiedler
ERCIM NEWS, 30-31, 2018
12018
From Monitoring, Logging, and Network Analysis to Threat Intelligence Extraction
I Friedberg, M Wurzenberger, A Al Balushi, B Kang
Collaborative Cyber Threat Intelligence, 69-127, 2017
2017
The BAESE Testbed-Analytic Evaluation of It Security Tools in Specified Network Environments
M Wurzenberger, F Skopik
ERCIM NEWS, 51-52, 2016
2016
Beyond gut instincts: Understanding, rating and comparing self-learning IDSs
M Wurzenberger, F Skopik, G Settanni, R Fiedler
2015 International Conference on Cyber Situational Awareness, Data Analytics …, 2015
2015
A Framework for Cyber Threat Intelligence Extraction from Raw Log Data
M Landauer, F Skopik, M Wurzenberger, W Hotwagner, A Rauber
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