Towards Blind Quantum Machine Learning in Entanglement Networks Abstract: Blind Quantum Computation (BQC) enables clients to delegate quantum computations to a quantum server while maintaining the privacy of their data and algorithms, even when the server is untrusted. In this work, we extend BQC frameworks to Quantum Machine Learning (QML) by implementing a network of […]

Quantumnetsec: Quantum machine learning for network security Abstract: As the digital landscape becomes increasingly complex, traditional cybersecurity measures are struggling to keep pace with the growing sophistication of cyber threats. This escalating challenge calls for new, more robust solutions. In this context, quantum computing emerges as a powerful tool that can change our approach to

Rede Generativa Adversarial Quântica Semi-Supervisionada (sQGAN) para Detecção de Ataques Resumo: A evolução das ameaças cibernéticas exige sistemas de detecção de ataques eficientes e precisos, mas a escassez de dados rotulados limita o uso de modelos supervisionados convencionais. Este artigo propõe a Rede Generativa Adversarial Quântica Semi-Supervisionada (sQGAN) para detecção de ataques, que combina aprendizado

QML-IDS: Quantum machine learning intrusion detection system Abstract: The emergence of quantum computing and related technologies presents opportunities for enhancing network security. The transition towards quantum computational power paves the way for creating strategies to mitigate the constantly advancing threats to network integrity. In response to this technological advancement, our research presents QML-IDS, a novel