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Florian Skopik

AIT Austrian Institute of Technology GmbH

Austria

Research Interests

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Professors in Austria Professors in Cybersecurity Cybersecurity professors in Austria

Articles (20)

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2026

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2025

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2021

Collaborators (9)

Edgar Weippl

Full Professor

Universität Wien

AUSTRIA

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LAM PHAM

AIT Austrian Institute of Technology GmbH

AUSTRIA

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Markus Wurzenberger

AIT Austrian Institute of Technology GmbH

AUSTRIA

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Max Landauer

AIT Austrian Institute of Technology GmbH

AUSTRIA

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Gregor Langner

AIT Austrian Institute of Technology GmbH

AUSTRIA

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Branka Stojanović

Head of Resilient Networks and Systems Competence Group

Joanneum Research Forschungsgesellschaft mbH

AUSTRIA

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Paul Smith

Lancaster University

UNITED KINGDOM

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Wolfgang Hotwagner

AIT Austrian Institute of Technology GmbH

AUSTRIA

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Daniel Slamanig

Full Professor of Cryptology

Bundeswehr University Munich

GERMANY

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Florian Skopik

Research Interests

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Articles (20)

Collaborative anomaly detection in log data: Comparative analysis and evaluation framework

Identifying Open-Source Threat Detection Resources on GitHub: A Scalable Machine Learning Approach

Trace of the Times: Rootkit Detection through Temporal Anomalies in Kernel Activity

A Comprehensive Survey with Critical Analysis for Deepfake Speech Detection

Towards a single device for multiple security domains

A review of time-series analysis for cyber security analytics: from intrusion detection to attack prediction

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

A logging maturity and decision model for the selection of intrusion detection cyber security solutions

Anomaly detection in log-event sequences: A federated deep learning approach and open challenges

Operational cyber incident coordination revisited: providing cyber situational awareness across organizations and countries

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

Maintainable Log Datasets for Evaluation of Intrusion Detection Systems

Deep learning for anomaly detection in log data: A survey

AMiner: A Modular Log Data Analysis Pipeline for Anomaly-based Intrusion Detection

Blind Spots of Security Monitoring in Enterprise Infrastructures: A Survey

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

From scattered data to actionable knowledge: flexible cyber security reporting in the military domain

The Seven Golden Principles of Effective Anomaly-Based Intrusion Detection

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

Enabling exercises, education and research with a comprehensive cyber range

Collaborators (9)

Edgar Weippl

LAM PHAM

Markus Wurzenberger

Max Landauer

Gregor Langner

Branka Stojanović

Paul Smith

Wolfgang Hotwagner

Daniel Slamanig

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