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		<title>Concrete Autoencoder Framework Sharpens Intrusion Detection for SDN-IoT Networks</title>
		<link>https://bioengineer.org/concrete-autoencoder-framework-sharpens-intrusion-detection-for-sdn-iot-networks/</link>
		
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		<pubDate>Sun, 25 Oct 2026 17:54:23 +0000</pubDate>
				<category><![CDATA[Technology]]></category>
		<category><![CDATA[autoencoders-based]]></category>
		<category><![CDATA[CAE-IDS]]></category>
		<category><![CDATA[concrete]]></category>
		<category><![CDATA[detection]]></category>
		<category><![CDATA[feature]]></category>
		<category><![CDATA[intrusion]]></category>
		<category><![CDATA[networks]]></category>
		<category><![CDATA[scientific research]]></category>
		<category><![CDATA[SDN-IoT]]></category>
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					<description><![CDATA[Researchers have introduced CAE-IDS, an intrusion detection framework that pairs a Concrete Autoencoder-based feature selection mechanism with Bayesian hyperparameter optimization, reporting up to 98.93% accuracy and a 98.92% F1-score across binary and multi-class classification tasks on two real-world datasets.]]></description>
		
		
		
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