The Proposition and Evaluation of the RoEduNet-SIMARGL2021 Network Intrusion Detection Dataset
| Autor: | Mihai Carabas, Mikołaj Komisarek, Darius Mihai, Witold Hołubowicz, Rafał Kozik, Marek Pawlicki, Maria-Elena Mihailescu |
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| Rok vydání: | 2021 |
| Předmět: |
Computer science
Arms race Stability (learning theory) Proposition TP1-1185 02 engineering and technology Intrusion detection system computer.software_genre Biochemistry Article Analytical Chemistry Machine Learning Constant (computer programming) 0202 electrical engineering electronic engineering information engineering dataset Network intrusion detection Electrical and Electronic Engineering Architecture Instrumentation Computer Security Chemical technology 020206 networking & telecommunications Atomic and Molecular Physics and Optics 020201 artificial intelligence & image processing Data mining computer network intrusion detection |
| Zdroj: | Sensors (Basel, Switzerland) Sensors Volume 21 Issue 13 Sensors, Vol 21, Iss 4319, p 4319 (2021) |
| ISSN: | 1424-8220 |
| DOI: | 10.3390/s21134319 |
| Popis: | Cybersecurity is an arms race, with both the security and the adversaries attempting to outsmart one another, coming up with new attacks, new ways to defend against those attacks, and again with new ways to circumvent those defences. This situation creates a constant need for novel, realistic cybersecurity datasets. This paper introduces the effects of using machine-learning-based intrusion detection methods in network traffic coming from a real-life architecture. The main contribution of this work is a dataset coming from a real-world, academic network. Real-life traffic was collected and, after performing a series of attacks, a dataset was assembled. The dataset contains 44 network features and an unbalanced distribution of classes. In this work, the capability of the dataset for formulating machine-learning-based models was experimentally evaluated. To investigate the stability of the obtained models, cross-validation was performed, and an array of detection metrics were reported. The gathered dataset is part of an effort to bring security against novel cyberthreats and was completed in the SIMARGL project. |
| Databáze: | OpenAIRE |
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