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	<title>privacy preservation &#8211; BIOENGINEER.ORG</title>
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		<title>Hybrid AI Model Catches Zero-Day DDoS Attacks in Smart Hospitals Without Exposing Patient Data</title>
		<link>https://bioengineer.org/hybrid-ai-model-catches-zero-day-ddos-attacks-in-smart-hospitals-without-exposing-patient-data/</link>
		
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		<pubDate>Thu, 08 Oct 2026 21:05:52 +0000</pubDate>
				<category><![CDATA[Technology]]></category>
		<category><![CDATA[Explainable AI]]></category>
		<category><![CDATA[federated learning]]></category>
		<category><![CDATA[FedProx]]></category>
		<category><![CDATA[healthcare IoT]]></category>
		<category><![CDATA[Industry 5.0]]></category>
		<category><![CDATA[intrusion detection]]></category>
		<category><![CDATA[LSTM]]></category>
		<category><![CDATA[privacy preservation]]></category>
		<category><![CDATA[SHAP]]></category>
		<category><![CDATA[software-defined networking]]></category>
		<category><![CDATA[Variational Autoencoder]]></category>
		<category><![CDATA[zero-day DDoS]]></category>
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					<description><![CDATA[Researchers have built a federated, explainable VAE-LSTM framework that detects previously unseen DDoS attacks in software-defined healthcare networks with over 98 percent accuracy while keeping patient data on-device.]]></description>
		
		
		
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