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 <channel rdf:about="http://ebiquity.umbc.edu//tags/html/?t=personally+identifiable+information">
  <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/" />
  <title><![CDATA[UMBC ebiquity RSS Tag Search]]></title>
  <link><![CDATA[http://ebiquity.umbc.edu//tags/html/?t=personally+identifiable+information]]></link>
  <description><![CDATA[UMBC ebiquity RSS Tag Search for personally identifiable information]]></description>
  <items>
    <rdf:Seq>
      <rdf:li resource="http://ebiquity.umbc.edu/project/html/id/107/Data-Privacy-management-using-Policy-compliant-Blockchain-structures"/>
      <rdf:li resource="http://ebiquity.umbc.edu/project/html/id/111/Medical-Device-Regulatory-Compliance"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1212/TRUCE-TRUsted-Compliance-Enforcement-Service-for-Secure-Health-Data-Exchange"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/961/Measuring-Semantic-Similarity-across-EU-GDPR-Regulation-and-Cloud-Privacy-Policies"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/843/An-Integrated-Knowledge-Graph-to-Automate-GDPR-and-PCI-DSS-Compliance"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/764/Semantic-Approach-to-Automating-Management-of-Big-Data-Privacy-Policies"/>
    </rdf:Seq>
  </items>
 </channel>
 <item rdf:about="http://ebiquity.umbc.edu/project/html/id/107/Data-Privacy-management-using-Policy-compliant-Blockchain-structures">
  <title><![CDATA[Data Privacy management using Policy compliant Blockchain structures]]></title>
  <link>http://ebiquity.umbc.edu/project/html/id/107/Data-Privacy-management-using-Policy-compliant-Blockchain-structures</link>
  <description><![CDATA[An important requirement of any information management system is to protect data and resources against leak or improper modifications, while at the same time ensure data availability to legitimate users. Moreover, systems handling personal data must also track its provenance and be regularly audited to comply with regulations. By assuring auditable, privacy policy compliant actions, we can also guarantee that areas where privacy policies have been technically enforced are highlighted.

As p...]]></description>
  <dc:date>2016-02-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/project/html/id/111/Medical-Device-Regulatory-Compliance">
  <title><![CDATA[Medical Device Regulatory Compliance]]></title>
  <link>http://ebiquity.umbc.edu/project/html/id/111/Medical-Device-Regulatory-Compliance</link>
  <description><![CDATA[Healthcare providers are deploying a large number of AI-driven Medical devices to help monitor and medicate patients. For patients with chronic ailments, like diabetes or gastric diseases, usage of these devices becomes part of their daily lifestyle. These medical devices often capture personally identifiable information (PII) and hence are strictly regulated by the Food and Drug Administration (FDA) to ensure the safety and efficacy of the medical device. Medical device regulations are curre...]]></description>
  <dc:date>2023-08-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1212/TRUCE-TRUsted-Compliance-Enforcement-Service-for-Secure-Health-Data-Exchange">
  <title><![CDATA[TRUCE: TRUsted Compliance Enforcement Service for Secure Health Data Exchange]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1212/TRUCE-TRUsted-Compliance-Enforcement-Service-for-Secure-Health-Data-Exchange</link>
  <description><![CDATA[Organizations are increasingly sharing large volumes of sensitive Personally Identifiable Information (PII), like health records, with each other to better manage their services. Protecting PII data has become increasingly important in today's digital age, and several regulations have been formulated to ensure the secure exchange and management of sensitive personal data. However, at times some of these regulations are at loggerheads with each other, like the Health Insurance Portability and ...]]></description>
  <dc:date>2025-12-09</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/961/Measuring-Semantic-Similarity-across-EU-GDPR-Regulation-and-Cloud-Privacy-Policies">
  <title><![CDATA[Measuring Semantic Similarity across EU GDPR Regulation and Cloud Privacy Policies]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/961/Measuring-Semantic-Similarity-across-EU-GDPR-Regulation-and-Cloud-Privacy-Policies</link>
  <description><![CDATA[Data protection authorities formulate policies and rules which the service providers have to comply with to ensure security and privacy when they perform Big Data analytics using users Personally Identifiable Information (PII). The knowledge contained in the data regulations and organizational privacy policies are typically maintained as short unstructured text in HTML or PDF formats. Hence it is an open challenge to determine the specific regulation rules that are being addressed by a provid...]]></description>
  <dc:date>2020-12-13</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/843/An-Integrated-Knowledge-Graph-to-Automate-GDPR-and-PCI-DSS-Compliance">
  <title><![CDATA[An Integrated Knowledge Graph to Automate GDPR and PCI DSS Compliance]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/843/An-Integrated-Knowledge-Graph-to-Automate-GDPR-and-PCI-DSS-Compliance</link>
  <description><![CDATA[Big data analytics related to consumer behavior,
market analysis, opinions, and recommendation often deal with
end user's derived and inferred data, along with the observed
data. To ensure consumer data protection, rules defined by the
European Union’s General Data Protection Regulation (EU
GDPR) must be adhered to by every organization
using Personally Identifiable Information (PII) data for Big
Data analysis. Similarly, Payment Card Industry Data Security
Standard (PCI DSS) has po...]]></description>
  <dc:date>2018-12-11</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/764/Semantic-Approach-to-Automating-Management-of-Big-Data-Privacy-Policies">
  <title><![CDATA[Semantic Approach to Automating Management of Big Data Privacy Policies]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/764/Semantic-Approach-to-Automating-Management-of-Big-Data-Privacy-Policies</link>
  <description><![CDATA[Ensuring the privacy of Big Data managed on the cloud is critical to ensure consumer confidence. Cloud providers publish privacy policy documents outlining the steps they take to ensure data and consumer privacy. These documents are available as large text documents that require manual effort and time to track and manage. We have developed a semantically rich ontology to describe the privacy policy documents and built a database of several policy documents as instances of this ontology. We ne...]]></description>
  <dc:date>2016-12-02</dc:date>
 </item>
</rdf:RDF>
