Comparison of feature extraction tools for network traffic data

Fuente: arXiv
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Autori principali: Lypa, Borys, Horyn, Ivan, Zagorodna, Natalia, Tymoshchuk, Dmytro, Lechachenko, Taras
Natura: Preprint
Pubblicazione: 2025
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author Lypa, Borys
Horyn, Ivan
Zagorodna, Natalia
Tymoshchuk, Dmytro
Lechachenko, Taras
author_facet Lypa, Borys
Horyn, Ivan
Zagorodna, Natalia
Tymoshchuk, Dmytro
Lechachenko, Taras
contents The comparison analysis of the most popular tools to extract features from network traffic is conducted in this paper. Feature extraction plays a crucial role in Intrusion Detection Systems (IDS) because it helps to transform huge raw network data into meaningful and manageable features for analysis and detection of malicious activities. The good choice of feature extraction tool is an essential step in construction of Artificial Intelligence-based Intrusion Detection Systems (AI-IDS), which can help to enhance the efficiency, accuracy, and scalability of such systems.
format Preprint
id arxiv_https___arxiv_org_abs_2501_13004
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Comparison of feature extraction tools for network traffic data
Lypa, Borys
Horyn, Ivan
Zagorodna, Natalia
Tymoshchuk, Dmytro
Lechachenko, Taras
Cryptography and Security
The comparison analysis of the most popular tools to extract features from network traffic is conducted in this paper. Feature extraction plays a crucial role in Intrusion Detection Systems (IDS) because it helps to transform huge raw network data into meaningful and manageable features for analysis and detection of malicious activities. The good choice of feature extraction tool is an essential step in construction of Artificial Intelligence-based Intrusion Detection Systems (AI-IDS), which can help to enhance the efficiency, accuracy, and scalability of such systems.
title Comparison of feature extraction tools for network traffic data
topic Cryptography and Security
url https://arxiv.org/abs/2501.13004