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	<title>UNSW-NB15 dataset &#8211; BIOENGINEER.ORG</title>
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		<title>Hybrid AI model spots never-before-seen cyber attacks and explains its calls</title>
		<link>https://bioengineer.org/hybrid-ai-model-spots-never-before-seen-cyber-attacks-and-explains-its-calls/</link>
		
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		<pubDate>Tue, 06 Oct 2026 22:30:35 +0000</pubDate>
				<category><![CDATA[Technology]]></category>
		<category><![CDATA[adaptive fusion]]></category>
		<category><![CDATA[Attention Mechanism]]></category>
		<category><![CDATA[cybersecurity]]></category>
		<category><![CDATA[deep learning]]></category>
		<category><![CDATA[Explainable AI]]></category>
		<category><![CDATA[intrusion detection system]]></category>
		<category><![CDATA[LSTM]]></category>
		<category><![CDATA[network security]]></category>
		<category><![CDATA[SHAP]]></category>
		<category><![CDATA[Transformer]]></category>
		<category><![CDATA[UNSW-NB15 dataset]]></category>
		<category><![CDATA[zero-day attack detection]]></category>
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					<description><![CDATA[Researchers have developed ZD-HybridNet, a hybrid Transformer-LSTM deep learning framework that detects attack categories withheld from training and explains its decisions through attention signals and SHAP-based feature attribution.]]></description>
		
		
		
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