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Open access Sep 2026

A hybrid fuzzy logic-driven behavioral intrusion detection architecture integrating fuzzy clustering and adaptive machine learning for Zero-Trust networks

In current Zero-Trust architectures, detecting behavioral intrusions has become critical because traditional rule-based access control systems struggle to combat polymorphic, low-and-slow, and identity-spoofing attacks. Although machine learning technologies have advanced intrusion detection through behavioral pattern...

M. Kamran, A. A. Khan, Suneeza Hamid et al. · 0 citations
Open access Jul 2026

A hybrid deep learning and quantum computing framework enhances cybersecurity threat detection and analysis

In the face of increasingly sophisticated cyber threats in an interconnected world, the need for scalable, intelligent, real-time cybersecurity solutions is intensifying. While traditional deep learning, such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs), is effective for detecting anomal...

Abdel-Haleem Abdel-Aty, Mohammed Farsi, M. Hafez et al. · 0 citations

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