Slide
Centre Interdisciplinaire
de Recherche et d’Innovation
en Cybersécurité et Société
de Recherche et d’Innovation
en Cybersécurité et Société
1.
Kadi, A.; Moudoud, H.; Khoukhi, L.; Houda, Z. A. El
Quantum-Enhanced LSTM for Sequential Network Flow Analysis: A Hybrid Approach to DDoS Detection Proceedings Article
In: Proc. - Int. Conf. Quantum Commun., Netw., Comput., QCNC, pp. 830–834, Institute of Electrical and Electronics Engineers Inc., 2026, ISBN: 979-833156110-9 (ISBN), (Journal Abbreviation: Proc. - Int. Conf. Quantum Commun., Netw., Comput., QCNC).
Abstract | Links | BibTeX | Tags: Denialof- service attacks, Distributed computer systems, Distributed denial of service, Distributed denial-of-service, Distributed Denial-of-Service (DDoS), Hybrid approach, Intrusion Detection, Learning systems, Logic gates, Long short-term memory, Machine-learning, Memory architecture, Network architecture, Network flow analysis, Network security, QLSTM, Quantum entanglement, Quantum machine learning, Quantum Machine Learning(QML), Quantum machines, Qubits, short term memory
@inproceedings{kadiQuantumEnhancedLSTMSequential2026,
title = {Quantum-Enhanced LSTM for Sequential Network Flow Analysis: A Hybrid Approach to DDoS Detection},
author = {A. Kadi and H. Moudoud and L. Khoukhi and Z. A. El Houda},
url = {https://www.scopus.com/pages/publications/105040813271?origin=resultslist},
doi = {10.1109/QCNC69040.2026.00136},
isbn = {979-833156110-9 (ISBN)},
year = {2026},
date = {2026-01-01},
booktitle = {Proc. - Int. Conf. Quantum Commun., Netw., Comput., QCNC},
pages = {830–834},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {Distributed Denial-of-Service (DDoS) attacks continue to grow at a rapid rate, making timely and reliable detection a challenge for intrusion detection systems (IDSs). Classical deep models such as Long Short-Term Memory (LSTM) can capture temporal dependencies; however, they still struggle with highly nonlinear and noisy flow dynamics, especially when attack patterns shift. To address this, we propose QLSTM-E, an enhanced hybrid quantum-classical architecture for network intrusion detection that uses Variational Quantum Circuits (VQCs) and LSTM modeling to learn complex temporal dependencies in network traffic. QLSTM-E exploits quantum characteristics, including superposition and entanglement, to improve the representation of nonlinear patterns in sequential flow features. To balance expressivity and circuit cost on near-term devices, we adopt an angle-based encoding strategy and a star-topology entangling layout that reduces two-qubit gate overhead while preserving effective quantum correlations. We implement QLSTM-E using PennyLane and Qiskit and evaluate it on the CIC-DDoS2019 dataset under a fully simulated setting, requiring no access to quantum hardware. Experimental results demonstrate strong detection effectiveness, achieving 99.7% accuracy and F1-score, and show strong robustness under depolarizing noise up to p= 0.1. © 2026 IEEE.},
note = {Journal Abbreviation: Proc. - Int. Conf. Quantum Commun., Netw., Comput., QCNC},
keywords = {Denialof- service attacks, Distributed computer systems, Distributed denial of service, Distributed denial-of-service, Distributed Denial-of-Service (DDoS), Hybrid approach, Intrusion Detection, Learning systems, Logic gates, Long short-term memory, Machine-learning, Memory architecture, Network architecture, Network flow analysis, Network security, QLSTM, Quantum entanglement, Quantum machine learning, Quantum Machine Learning(QML), Quantum machines, Qubits, short term memory},
pubstate = {published},
tppubtype = {inproceedings}
}
Distributed Denial-of-Service (DDoS) attacks continue to grow at a rapid rate, making timely and reliable detection a challenge for intrusion detection systems (IDSs). Classical deep models such as Long Short-Term Memory (LSTM) can capture temporal dependencies; however, they still struggle with highly nonlinear and noisy flow dynamics, especially when attack patterns shift. To address this, we propose QLSTM-E, an enhanced hybrid quantum-classical architecture for network intrusion detection that uses Variational Quantum Circuits (VQCs) and LSTM modeling to learn complex temporal dependencies in network traffic. QLSTM-E exploits quantum characteristics, including superposition and entanglement, to improve the representation of nonlinear patterns in sequential flow features. To balance expressivity and circuit cost on near-term devices, we adopt an angle-based encoding strategy and a star-topology entangling layout that reduces two-qubit gate overhead while preserving effective quantum correlations. We implement QLSTM-E using PennyLane and Qiskit and evaluate it on the CIC-DDoS2019 dataset under a fully simulated setting, requiring no access to quantum hardware. Experimental results demonstrate strong detection effectiveness, achieving 99.7% accuracy and F1-score, and show strong robustness under depolarizing noise up to p= 0.1. © 2026 IEEE.
2.
Warren, C. M.; Breuer, A. T.; Kantner, J.; Fiset, D.; Blais, C.; Masson, M. E. J.
Target-distractor interference in the attentional blink implicates the locus coeruleus-norepinephrine system Journal Article
In: Psychonomic Bulletin and Review, vol. 16, no. 6, pp. 1106–1111, 2009, ISSN: 10699384.
Abstract | Links | BibTeX | Tags: article, Attentional Blink, human, Humans, Learning, locus ceruleus, Locus Coeruleus, Memory, Models, noradrenalin, Norepinephrine, Pattern Recognition, perception, Perceptual Masking, physiology, Psychological, psychological model, Psychophysics, reaction time, Serial Learning, short term memory, Short-Term, Visual
@article{warren_target-distractor_2009,
title = {Target-distractor interference in the attentional blink implicates the locus coeruleus-norepinephrine system},
author = {C. M. Warren and A. T. Breuer and J. Kantner and D. Fiset and C. Blais and M. E. J. Masson},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-74849134787&doi=10.3758%2fPBR.16.6.1106&partnerID=40&md5=dedfbcb0f338038cbcaedefcbc9d184f},
doi = {10.3758/PBR.16.6.1106},
issn = {10699384},
year = {2009},
date = {2009-01-01},
journal = {Psychonomic Bulletin and Review},
volume = {16},
number = {6},
pages = {1106–1111},
abstract = {We provide evidence that the locus coeruleus-norephinephrine (LC-NE) system is the neurophysiological basis of the attentional blink. The attentional blink refers to decreased accuracy for reporting the second of two targets in a rapid serial visual presentation of distractors. The LC-NE account of the attentional blink posits that targets elicit a facilitative LC-NE system response that is available for the first target but subsequently unavailable to the second, due to the autoinhibitory nature of the LC-NE system. We propose a modification of the LC-NE account, suggesting that the LC-NE system response is elicited by interference between mutually exclusive responses demanded by temporally proximal targets and distractors. We increased the interference between the first target and the following distractor by reducing the time between them. For identifying the second target this high-interference condition yielded a benefit up to 200 msec after onset of the first, followed by a decrease in accuracy. Consistent with our modification of the LC-NE account, this result suggests a temporarily enhanced LC-NE system response to increased target-distractor interference. © 2009 The Psychonomic Society, Inc.},
keywords = {article, Attentional Blink, human, Humans, Learning, locus ceruleus, Locus Coeruleus, Memory, Models, noradrenalin, Norepinephrine, Pattern Recognition, perception, Perceptual Masking, physiology, Psychological, psychological model, Psychophysics, reaction time, Serial Learning, short term memory, Short-Term, Visual},
pubstate = {published},
tppubtype = {article}
}
We provide evidence that the locus coeruleus-norephinephrine (LC-NE) system is the neurophysiological basis of the attentional blink. The attentional blink refers to decreased accuracy for reporting the second of two targets in a rapid serial visual presentation of distractors. The LC-NE account of the attentional blink posits that targets elicit a facilitative LC-NE system response that is available for the first target but subsequently unavailable to the second, due to the autoinhibitory nature of the LC-NE system. We propose a modification of the LC-NE account, suggesting that the LC-NE system response is elicited by interference between mutually exclusive responses demanded by temporally proximal targets and distractors. We increased the interference between the first target and the following distractor by reducing the time between them. For identifying the second target this high-interference condition yielded a benefit up to 200 msec after onset of the first, followed by a decrease in accuracy. Consistent with our modification of the LC-NE account, this result suggests a temporarily enhanced LC-NE system response to increased target-distractor interference. © 2009 The Psychonomic Society, Inc.
3.
Warren, C. M.; Breuer, A. T.; Kantner, J.; Fiset, D.; Blais, C.; Masson, M. E. J.
Target-distractor interference in the attentional blink implicates the locus coeruleus-norepinephrine system Journal Article
In: Psychonomic Bulletin and Review, vol. 16, no. 6, pp. 1106–1111, 2009, ISSN: 10699384.
Abstract | Links | BibTeX | Tags: article, Attentional Blink, human, Humans, Learning, locus ceruleus, Locus Coeruleus, Memory, Models, noradrenalin, Norepinephrine, Pattern Recognition, perception, Perceptual Masking, physiology, Psychological, psychological model, Psychophysics, reaction time, Serial Learning, short term memory, Short-Term, Visual
@article{warrenTargetdistractorInterferenceAttentional2009,
title = {Target-distractor interference in the attentional blink implicates the locus coeruleus-norepinephrine system},
author = {C. M. Warren and A. T. Breuer and J. Kantner and D. Fiset and C. Blais and M. E. J. Masson},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-74849134787&doi=10.3758%2fPBR.16.6.1106&partnerID=40&md5=dedfbcb0f338038cbcaedefcbc9d184f},
doi = {10.3758/PBR.16.6.1106},
issn = {10699384},
year = {2009},
date = {2009-01-01},
journal = {Psychonomic Bulletin and Review},
volume = {16},
number = {6},
pages = {1106–1111},
abstract = {We provide evidence that the locus coeruleus-norephinephrine (LC-NE) system is the neurophysiological basis of the attentional blink. The attentional blink refers to decreased accuracy for reporting the second of two targets in a rapid serial visual presentation of distractors. The LC-NE account of the attentional blink posits that targets elicit a facilitative LC-NE system response that is available for the first target but subsequently unavailable to the second, due to the autoinhibitory nature of the LC-NE system. We propose a modification of the LC-NE account, suggesting that the LC-NE system response is elicited by interference between mutually exclusive responses demanded by temporally proximal targets and distractors. We increased the interference between the first target and the following distractor by reducing the time between them. For identifying the second target this high-interference condition yielded a benefit up to 200 msec after onset of the first, followed by a decrease in accuracy. Consistent with our modification of the LC-NE account, this result suggests a temporarily enhanced LC-NE system response to increased target-distractor interference. © 2009 The Psychonomic Society, Inc.},
keywords = {article, Attentional Blink, human, Humans, Learning, locus ceruleus, Locus Coeruleus, Memory, Models, noradrenalin, Norepinephrine, Pattern Recognition, perception, Perceptual Masking, physiology, Psychological, psychological model, Psychophysics, reaction time, Serial Learning, short term memory, Short-Term, Visual},
pubstate = {published},
tppubtype = {article}
}
We provide evidence that the locus coeruleus-norephinephrine (LC-NE) system is the neurophysiological basis of the attentional blink. The attentional blink refers to decreased accuracy for reporting the second of two targets in a rapid serial visual presentation of distractors. The LC-NE account of the attentional blink posits that targets elicit a facilitative LC-NE system response that is available for the first target but subsequently unavailable to the second, due to the autoinhibitory nature of the LC-NE system. We propose a modification of the LC-NE account, suggesting that the LC-NE system response is elicited by interference between mutually exclusive responses demanded by temporally proximal targets and distractors. We increased the interference between the first target and the following distractor by reducing the time between them. For identifying the second target this high-interference condition yielded a benefit up to 200 msec after onset of the first, followed by a decrease in accuracy. Consistent with our modification of the LC-NE account, this result suggests a temporarily enhanced LC-NE system response to increased target-distractor interference. © 2009 The Psychonomic Society, Inc.