Florian Skopik

AIT Austrian Institute of Technology GmbH

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Articles (20)

Collaborators (7)

Edgar Weippl

Full Professor

Universität Wien

Markus Wurzenberger

AIT Austrian Institute of Technology GmbH

Max Landauer

AIT Austrian Institute of Technology GmbH

Gregor Langner

AIT Austrian Institute of Technology GmbH

Paul Smith

Lancaster University

UNITED KINGDOM

Wolfgang Hotwagner

AIT Austrian Institute of Technology GmbH

Daniel Slamanig

Full Professor of Cryptology

Bundeswehr University Munich

Florian Skopik

Research Interests

Explore related searches

Contact this professor

Articles (20)

Collaborators (7)

Edgar Weippl

Markus Wurzenberger

Max Landauer

Gregor Langner

Paul Smith

Wolfgang Hotwagner

Daniel Slamanig

How do I reach out?

Meet Kite AI

Florian Skopik

Research Interests

Explore related searches

Contact this professor

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 (7)

Edgar Weippl

Markus Wurzenberger

Max Landauer

Gregor Langner

Paul Smith

Wolfgang Hotwagner

Daniel Slamanig

How do I reach out?

Meet Kite AI