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      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1210/Security-Compliance-for-Smart-Manufacturing-using-Knowledgegraph-based-Digital-Twin"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1135/Change-Management-using-Generative-Modeling-on-Digital-Twins"/>
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 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1210/Security-Compliance-for-Smart-Manufacturing-using-Knowledgegraph-based-Digital-Twin">
  <title><![CDATA[Security Compliance for Smart Manufacturing using Knowledgegraph based Digital Twin]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1210/Security-Compliance-for-Smart-Manufacturing-using-Knowledgegraph-based-Digital-Twin</link>
  <description><![CDATA[The combination of Information Technology (IT) and Operational Technology (OT) in smart manufacturing, driven by smart factory innovations and Internet of Things (IoT) devices, generates vast, diverse, and rapidly evolving Big Data, which in turn increases cybersecurity and compliance issues. Adherence to security standards, such as NIST SP 800-171, which requires rigorous access control and audit reporting, is currently obstructed by the resource-intensive and error-prone aspects of manual e...]]></description>
  <dc:date>2025-12-11</dc:date>
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 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1135/Change-Management-using-Generative-Modeling-on-Digital-Twins">
  <title><![CDATA[Change Management using Generative Modeling on Digital Twins]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1135/Change-Management-using-Generative-Modeling-on-Digital-Twins</link>
  <description><![CDATA[A key challenge faced by small and medium-sized business entities is securely managing software updates and changes. Specifically, with rapidly evolving cybersecurity threats, changes/updates/patches to software systems are necessary to stay ahead of emerging threats and are often mandated by regulators or statutory authorities to counter these. However, security patches/updates require stress testing before they can be released in the production system. Stress testing in production environme...]]></description>
  <dc:date>2023-10-02</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/994/Cyber-Physical-System-Security-Surveillance-using-Knowledge-Graph-based-Digital-Twins-A-Smart-Farming-Usecase">
  <title><![CDATA[Cyber-Physical System Security Surveillance using Knowledge Graph based Digital Twins - A Smart Farming Usecase]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/994/Cyber-Physical-System-Security-Surveillance-using-Knowledge-Graph-based-Digital-Twins-A-Smart-Farming-Usecase</link>
  <description><![CDATA[Rapid advancements in Cyber-Physical System (CPS) capabilities have motivated farmers to deploy this ecosystem on their farms. However, there is a growing concern among users regarding the security risks associated with CPS. Especially with rising number of cyber-attacks on CPS, such as modifying sensor readings, interrupting operations, etc. Therefore, this paper describes a security surveillance framework to detect deviations in the ecosystem by incorporating a digital twin supported anomal...]]></description>
  <dc:date>2021-08-31</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/779/Generating-Digital-Twin-models-using-Knowledge-Graphs-for-Industrial-Production-Lines">
  <title><![CDATA[Generating Digital Twin models using Knowledge Graphs for  Industrial Production Lines]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/779/Generating-Digital-Twin-models-using-Knowledge-Graphs-for-Industrial-Production-Lines</link>
  <description><![CDATA[Digital Twin models are computerized clones of physical assets that can be used for in-depth analysis. Industrial production lines tend to have multiple sensors to generate near real-time status information for production. Industrial Internet of Things datasets are difficult to analyze and infer valuable insights such as points of failure, estimated overhead. etc. In this paper we introduce a simple way of formalizing knowledge as digital twin models coming from sensors in industrial producti...]]></description>
  <dc:date>2017-06-25</dc:date>
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