Mikolaj Komisarek

Orcid: 0000-0003-1459-2695

According to our database1, Mikolaj Komisarek authored at least 11 papers between 2020 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of five.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2023
Modern NetFlow network dataset with labeled attacks and detection methods.
Proceedings of the 18th International Conference on Availability, Reliability and Security, 2023

2022
Hunting cyberattacks: experience from the real backbone network.
J. Wirel. Mob. Networks Ubiquitous Comput. Dependable Appl., 2022

The IoT Threat Landscape vs. Machine Learning, a.k.a. Who Attacks IoT, Why Do They Do It, and How to Prevent It?
Proceedings of the Information Systems Development: Artificial Intelligence for Information Systems Development and Operations (ISD2022 Proceedings), Cluj-Napoca, Romania, 31 August, 2022

A novel, refined dataset for real-time Network Intrusion Detection.
Proceedings of the ARES 2022: The 17th International Conference on Availability, Reliability and Security, Vienna,Austria, August 23, 2022

2021
The Proposition and Evaluation of the RoEduNet-SIMARGL2021 Network Intrusion Detection Dataset.
Sensors, 2021

Machine Learning Based Approach to Anomaly and Cyberattack Detection in Streamed Network Traffic Data.
J. Wirel. Mob. Networks Ubiquitous Comput. Dependable Appl., 2021

How to Effectively Collect and Process Network Data for Intrusion Detection?
Entropy, 2021

The Proposition of Balanced and Explainable Surrogate Method for Network Intrusion Detection in Streamed Real Difficult Data.
Proceedings of the Advances in Computational Collective Intelligence, 2021

Extending Machine Learning-Based Intrusion Detection with the Imputation Method.
Proceedings of the Progress in Image Processing, Pattern Recognition and Communication Systems, 2021

Network Intrusion Detection in the Wild - the Orange use case in the SIMARGL project.
Proceedings of the ARES 2021: The 16th International Conference on Availability, 2021

2020
Real-time stream processing tool for detecting suspicious network patterns using machine learning.
Proceedings of the ARES 2020: The 15th International Conference on Availability, 2020


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