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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2501.13004 |
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| _version_ | 1866910794695835648 |
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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 |