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1 2025

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Preliminary study on artificial intelligence methods for cybersecurity threat detection in computer networks based on raw data packets

Ogonowski Aleksander, Żebrowski Michał, Ćwiek Arkadiusz, Jarosiewicz Tobiasz, Klimaszewski Konrad, Padee Adam, Wasiuk Piotr, Wójcik Michał

Computer Science

2025

T. 26 (SI)

45-–68

Most of the intrusion detection methods in computer networks are based on traffic flow characteristics. However, this approach may not fully exploit the potential of deep learning algorithms to directly extract features and patterns from raw packets. Moreover, it impedes real-time monitoring due to the necessity of waiting for the processing pipeline to complete and introduces dependencies on additional software components. In this paper, we investigate deep learning methodologies capable of detecting attacks in real-time directly from raw packet data within network traffic. Our investigation utilizes the CICIDS-2017 dataset, which includes both benign traffic and prevalent real-world attacks, providing a comprehensive foundation for our research.