Optimized hybrid quantum–classical model for UDP attack detection in next-generation communication systems

Liang Zhou; Shin Hung Pan; Akshat Gaurav; Varsha Arya; Shahab S. Band; Kwok Tai Chui; Brij B. Gupta

doi:10.1016/j.icte.2026.05.009

Optimized hybrid quantum–classical model for UDP attack detection in next-generation communication systems

Liang Zhou
, Shin Hung Pan
, Akshat Gaurav
, Varsha Arya
, Shahab S. Band
, Kwok Tai Chui
, Brij B. Gupta

Electronic Engineering and Computer Science

Research output: Contribution to journal › Article › peer-review

Abstract

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%.

Original language	English
Journal	ICT Express
DOIs	https://doi.org/10.1016/j.icte.2026.05.009
Publication status	Accepted/In press - 2026

Keywords

CNN-LSTM
Hybrid quantum–classical model
Quantum machine learning
UDP attack detection
Virus colony search

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10.1016/j.icte.2026.05.009

Cite this

@article{0fb00cd3089243bba036f0ae81a7288b,

title = "Optimized hybrid quantum{\textendash}classical model for UDP attack detection in next-generation communication systems",

abstract = "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 = "CNN-LSTM, Hybrid quantum{\textendash}classical model, Quantum machine learning, UDP attack detection, Virus colony search",

author = "Liang Zhou and Pan, \{Shin Hung\} and Akshat Gaurav and Varsha Arya and Band, \{Shahab S.\} and Chui, \{Kwok Tai\} and Gupta, \{Brij B.\}",

note = "Publisher Copyright: Copyright {\textcopyright} 2026. Published by Elsevier B.V.",

year = "2026",

doi = "10.1016/j.icte.2026.05.009",

language = "English",

}

TY - JOUR

T1 - Optimized hybrid quantum–classical model for UDP attack detection in next-generation communication systems

AU - Zhou, Liang

AU - Pan, Shin Hung

AU - Gaurav, Akshat

AU - Arya, Varsha

AU - Band, Shahab S.

AU - Chui, Kwok Tai

AU - Gupta, Brij B.

PY - 2026

Y1 - 2026

N2 - 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%.

AB - 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%.

KW - CNN-LSTM

KW - Hybrid quantum–classical model

KW - Quantum machine learning

KW - UDP attack detection

KW - Virus colony search

UR - https://www.scopus.com/pages/publications/105040093721

U2 - 10.1016/j.icte.2026.05.009

DO - 10.1016/j.icte.2026.05.009

M3 - Article

AN - SCOPUS:105040093721

JO - ICT Express

JF - ICT Express

ER -

Optimized hybrid quantum–classical model for UDP attack detection in next-generation communication systems

Abstract

Keywords

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