<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Explainable-Ai on CuraSec</title><link>https://curasec.metacog.co.kr/tags/explainable-ai/</link><description>Recent content in Explainable-Ai on CuraSec</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Mon, 14 Sep 2026 18:03:45 +0000</lastBuildDate><atom:link href="https://curasec.metacog.co.kr/tags/explainable-ai/index.xml" rel="self" type="application/rss+xml"/><item><title>XAI Anomaly Detection Framework for DER/Power-Grid Networks (Research)</title><link>https://curasec.metacog.co.kr/insights/2026-09-14-self-verifying-anomaly-detection-using-explainable-ai-for-cy/</link><pubDate>Mon, 14 Sep 2026 18:03:45 +0000</pubDate><guid>https://curasec.metacog.co.kr/insights/2026-09-14-self-verifying-anomaly-detection-using-explainable-ai-for-cy/</guid><description>&lt;ul>
&lt;li>&lt;strong>Engineer — Skip&lt;/strong>&lt;/li>
&lt;li>&lt;strong>SOC/IR — Learn:&lt;/strong> Academic paper exploring SHAP-based self-verification to flag inconsistent ML anomaly detection alerts — the explainability-as-confidence-check pattern could inform future ML detection pipelines, but the OT/DNP3 domain is too niche for most enterprise SOC teams.&lt;/li>
&lt;li>&lt;strong>Leader — Skip&lt;/strong>&lt;/li>
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