Pattern Augmented Lightweight Convolutional Neural Network for Intrusion Detection System

As the world increasingly becomes more interconnected, the demand for safety and security is ever-increasing, particularly for industrial networks. This has prompted numerous researchers to investigate different methodologies and techniques suitable for intrusion detection systems (IDS) requirements...

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Veröffentlicht in:	Electronics (Basel) 2024-03, Vol.13 (5), p.932
Hauptverfasser:	Tadesse, Yonatan Embiza, Choi, Young-June
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Anomalies Artificial neural networks Classification Cybersecurity Data security Datasets Deep learning Denial of service attacks False alarms Fourier transforms Image quality Intrusion detection systems Lightweight Machine learning Malware Methods Neural networks Performance measurement Prevention Sensitivity
Online-Zugang:	Volltext
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