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20242026
most citedQuantum Clustering for Cybersecurity

15 citations · 24 across the 10 of their papers we have counts for

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5 papers · 1 filter

quant-ph2026

QBFF: Deep Quantum Bottleneck for Automatic Speaker Verification Anti-Spoofing

Anton Firc, Nouhaila Innan, Vojtěch Staněk +6

A central goal of quantum machine learning is to identify applications in which small quantum circuits can improve task performance while remaining executable on real hardware. We…

quant-ph2026

VQCSim: When Does Compile-Once Statevector Simulation Beat Generic Quantum Frameworks?

Anton Firc, Martin Perešíni, Vojtěch Mrázek +7

Hybrid quantum-classical machine learning workflows repeatedly evaluate many small parametrized circuits during training and model exploration. In this regime, framework dispatch a…

quant-ph2026

Q-RAIL: A Reliability-Aware Framework for Quantum Federated Learning on Heterogeneous Noisy Hardware

Walid El Maouaki, Muhammad Shafique

Quantum federated learning (QFL) on NISQ hardware is highly sensitive to backend heterogeneity: some clients contribute informative updates, while others contribute noise-dominated…

quant-ph2026

QGCL: Quantum-Guided Clause Learning for Cryptanalytic SAT

Walid El Maouaki, Alberto Marchisio, Muhammad Shafique

Power side-channel attacks on AES exploit data-dependent physical leakage to recover secret keys, but turning noisy leakage observations into a verified AES-128 key remains a hard…

quant-ph2026

Q-LEAK: Quantum-Based LEAKage Verification for Side-Channel Countermeasures

Walid El Maouaki, Alberto Marchisio, Muhammad Shafique

Formal verification of power side-channel leakage and its countermeasures in cryptographic algorithms is challenging, as SAT-based methods fail to scale on XOR-heavy, time-unrolled…