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Author

H. Al-Ofeishat

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Open access Oct 2026

Fast few-shot intrusion detection via depthwise meta-learning

Network intrusion detection systems (NIDS) increasingly rely on deep learning to cope with evolving cyber attacks, yet they typically require large amounts of labeled data per attack type and exhibit poor generalization to novel threats. Recent advances in meta-learning and few-shot learning have shown promise for alle...

H. Al-Ofeishat, Mamoon Obiedat, Ayooub Alsarhan et al. · 0 citations
Open access Aug 2026

Enhancing Vulnerability Detection Precision through Ensemble Learning with Large Language Models

The results show that the ensemble techniques are a practical approach to boost the precision of LLMs in the detection of vulnerabilities and suggest that ensemble methods offer great potential in the advancement of software security analysis.

H. Al-Ofeishat, Azhar Hussain, M. Faheem et al. · 0 citations

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