一种新颖、精细的实时网络入侵检测数据集

Mikołaj Komisarek, M. Pawlicki, Marian Mihailescu, Darius Mihai, M. Cărăbaş, R. Kozik, M. Choraś
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引用次数: 1

摘要

在这个互联网普及的时代,越来越多的经济领域依赖于网络技术的各个方面。网络犯罪呈上升趋势,每年都会发生大量的网络安全漏洞。本文介绍了以Netflow格式采集的网络数据及其在网络攻击检测中的应用。本文提出了一个从学术网络中收集的精炼的真实数据集。该数据集是通过使用simmargl2021数据集获得的经验的直接结果。在几种机器学习算法上证明了新数据集的适用性。这个新颖的数据集是开源的,供研究人员下载并用于科学工作。
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A novel, refined dataset for real-time Network Intrusion Detection
In this day and age of widespread Internet access, more and more aspects of the economy are becoming dependent on various aspects of network technologies. Cybercrimes are on the rise and massive numbers of network security breaches occur every year. This paper presents network data collected in the Netflow format and its application to detect network attacks. The paper proposes a refined, real-world dataset collected from an academic network. The dataset is a direct result from the experience gained by working on and with the SIMARGL2021 dataset. The applicability of the new dataset is demonstrated on several machine learning algorithms. This novel dataset is open-sourced for researchers to download and use in scientific work.
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