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Optimized hybrid quantum-classical model for UDP attack detection in next-generation communication systems
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DOI：10.1016/j.icte.2026.05.009.png)
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Abstract
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UDP flood attacks are getting more advanced. In modern networks, these attacks need smart and fast ways to be stopped. In this context, this paper introduces a hybrid model that combines CNN, LSTM and a quantum circuit. It is built to detect UDP-based threats early and with high accuracy. To choose the best features, the Virus Colony Search algorithm is used. The model also used embedding drift to improve categorical features. The quantum layer was tested using Pauli-Z output Bloch vectors and gate rotation values. The model achieves a high accuracy of 99.97%.
Keywords:
Quantum machine learning
UDP attack detection
Hybrid quantum–classical model
CNN-LSTM
Virus colony search
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