<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Reinforcement-Learning on CuraSec</title><link>https://curasec.metacog.co.kr/tags/reinforcement-learning/</link><description>Recent content in Reinforcement-Learning on CuraSec</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Mon, 02 Nov 2026 21:42:19 +0000</lastBuildDate><atom:link href="https://curasec.metacog.co.kr/tags/reinforcement-learning/index.xml" rel="self" type="application/rss+xml"/><item><title>ADS-OT: RL-Based Adaptive Defense Framework for OT Against AI Attacks</title><link>https://curasec.metacog.co.kr/insights/2026-11-02-adaptive-dynamic-security-for-operational-technology-against/</link><pubDate>Mon, 02 Nov 2026 21:42:19 +0000</pubDate><guid>https://curasec.metacog.co.kr/insights/2026-11-02-adaptive-dynamic-security-for-operational-technology-against/</guid><description>&lt;ul>
&lt;li>&lt;strong>Engineer — Learn:&lt;/strong> Academic framework applying reinforcement learning to OT defensive posture (monitoring, segmentation, deception) — no implementation artifact to deploy today, but relevant if you own ICS/OT infrastructure and are thinking about adaptive controls architecture.&lt;/li>
&lt;li>&lt;strong>SOC/IR — Skip&lt;/strong>&lt;/li>
&lt;li>&lt;strong>Leader — Learn:&lt;/strong> Research framing AI-accelerated attack tempo against OT as a design-level problem; useful background for leaders with ICS/SCADA exposure when building the case for adaptive OT security investment, but too early-stage to drive near-term decisions.&lt;/li>
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