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	<title>IOTTRUST &#8211; BIOENGINEER.ORG</title>
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		<title>Graph Topology Gives IoT Intrusion Detection a Hidden Edge</title>
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		<pubDate>Sat, 17 Oct 2026 13:32:03 +0000</pubDate>
				<category><![CDATA[Technology]]></category>
		<category><![CDATA[Anomaly]]></category>
		<category><![CDATA[community detection]]></category>
		<category><![CDATA[detection]]></category>
		<category><![CDATA[False positive reduction]]></category>
		<category><![CDATA[graph-based]]></category>
		<category><![CDATA[graph-based anomaly detection]]></category>
		<category><![CDATA[intrusion detection]]></category>
		<category><![CDATA[IoT security]]></category>
		<category><![CDATA[IOTTRUST]]></category>
		<category><![CDATA[Machine Learning]]></category>
		<category><![CDATA[network topology]]></category>
		<category><![CDATA[UNSW-NB15]]></category>
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					<description><![CDATA[A graph-augmented framework called IOTTRUST enriches conventional IoT intrusion detection with network flow topology features, achieving 99.07 percent accuracy and a reduced false alarm rate on UNSW-NB15 under a strict leakage-free evaluation.]]></description>
		
		
		
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