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	This ontology document is licensed under the Creative Commons
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 <channel rdf:about="http://ebiquity.umbc.edu//tags/html/?t=data+privacy">
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  <title><![CDATA[UMBC ebiquity RSS Tag Search]]></title>
  <link><![CDATA[http://ebiquity.umbc.edu//tags/html/?t=data+privacy]]></link>
  <description><![CDATA[UMBC ebiquity RSS Tag Search for data privacy]]></description>
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      <rdf:li resource="http://ebiquity.umbc.edu/conference/html/id/3/ACM-SIGMOD-PODS-2004-Conference"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/484/Semantic-knowledge-and-privacy-in-the-physical-web"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/456/Energy-efficient-semantic-context-model-for-managing-privacy-on-smartphones"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/457/Energy-efficient-semantic-context-model-for-managing-privacy-on-smartphones"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/450/An-energy-efficient-semantic-context-model-for-managing-privacy-on-smartphones"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/312/Privacy-Preserving-Distributed-Data-Mining-A-Multi-objective-Optimization-and-Algorithmic-Game-theoretic-Approach"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/223/A-Game-Theoretic-Framework-for-Distributed-Multi-Party-Privacy-Preserving-Data-Mining"/>
      <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/112/Online-Health-Information"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1221/Deontic-Policies-for-Runtime-Governance-of-Agentic-AI-Systems"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1200/Automating-IoT-Data-Privacy-Compliance-by-Integrating-Knowledge-Graphs-With-Large-Language-Models"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1179/KiNETGAN-Enabling-Distributed-Network-Intrusion-Detection-through-Knowledge-Infused-Synthetic-Data-Generation"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1128/Secure-and-Privacy-Compliant-Data-Sharing-An-Essential-Framework-for-Healthcare-Organizations"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1156/Privacy-Preserving-Data-Sharing-in-Agriculture-Enforcing-Policy-Rules-for-Secure-and-Confidential-Data-Synthesis"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1127/IoT-Reg-A-Comprehensive-Knowledge-Graph-for-Real-Time-IoT-Data-Privacy-Compliance"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1024/Semantically-Rich-Access-Control-in-Cloud-EHR-Systems-Based-on-MA-ABE"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/889/Automating-GDPR-Compliance-using-Policy-Integrated-Blockchain"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/858/Multi-Authority-Access-Control-in-a-Cloud-EHR-System-with-MA-ABE"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/847/Automating-Privacy-Compliance-Using-Policy-Integrated-Blockchain"/>
      <rdf:li resource="http://ebiquity.umbc.edu/research/area/id/38/Blockchain"/>
      <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/370/Ontology-for-Data-Privacy-Policy"/>
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 <item rdf:about="http://ebiquity.umbc.edu/conference/html/id/3/ACM-SIGMOD-PODS-2004-Conference">
  <title><![CDATA[ACM SIGMOD/PODS 2004 Conference]]></title>
  <link>http://ebiquity.umbc.edu/conference/html/id/3/ACM-SIGMOD-PODS-2004-Conference</link>
  <description><![CDATA[The annual ACM SIGMOD conference is a leading forum for database researchers, practitioners, developers, and users to explore cutting-edge ideas and to exchange techniques, tools, and experiences. We invite the submission of original research contributions and industrial papers, as well as proposals for panels, tutorials, and demonstrations. We encourage submissions relating to all aspects of data management defined broadly, and particularly encourage work on topics of emerging interest in ...]]></description>
  <dc:date>2004-06-13</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/484/Semantic-knowledge-and-privacy-in-the-physical-web">
  <title><![CDATA[Semantic knowledge and privacy in the physical web]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/484/Semantic-knowledge-and-privacy-in-the-physical-web</link>
  <description><![CDATA[In the past few years, the Internet of Things has started to become a reality; however, its growth has been hampered by privacy and security concerns. One promising approach is to use Semantic Web technologies to mitigate privacy concerns in an informed, flexible way. We present CARLTON, a framework for managing data privacy for entities in a Physical Web deployment using Semantic Web technologies. CARLTON uses context-sensitive privacy policies to protect privacy of organizational and person...]]></description>
  <dc:date>2016-09-27</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/456/Energy-efficient-semantic-context-model-for-managing-privacy-on-smartphones">
  <title><![CDATA[Energy efficient semantic context model for managing privacy on smartphones]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/456/Energy-efficient-semantic-context-model-for-managing-privacy-on-smartphones</link>
  <description><![CDATA[Modern smartphones are capable of gathering massive amounts of data about a user and her context. While this data is mostly utilized for providing services that are better suited to the user, user data and context leakage from smart phones can have disastrous results. This is especially true as most enterprises are going to a Bring-Your-Own-Device (BYOD) model for mobile devices such as smartphones. We recognize this change as a potential threat to data privacy, both of the user and also of c...]]></description>
  <dc:date>2013-04-22</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/457/Energy-efficient-semantic-context-model-for-managing-privacy-on-smartphones">
  <title><![CDATA[Energy efficient semantic context model for managing privacy on smartphones]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/457/Energy-efficient-semantic-context-model-for-managing-privacy-on-smartphones</link>
  <description><![CDATA[Modern smartphones are capable of gathering massive amounts of data about a user and her context. While this data is mostly utilized for providing services that are better suited to the user, user data and context leakage from smart phones can have disastrous results. This is especially true as most enterprises are going to a Bring-Your-Own-Device (BYOD) model for mobile devices such as smartphones. We recognize this change as a potential threat to data privacy, both of the user and also of c...]]></description>
  <dc:date>2013-04-22</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/450/An-energy-efficient-semantic-context-model-for-managing-privacy-on-smartphones">
  <title><![CDATA[An energy efficient semantic context model for managing privacy on smartphones]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/450/An-energy-efficient-semantic-context-model-for-managing-privacy-on-smartphones</link>
  <description><![CDATA[Modern smartphones are capable of gathering massive amounts of data about a user and her context. While this data is mostly utilized for providing services that are better suited to the user, user data and context leakage from smart phones can have disastrous results. This is especially true as most enterprises are going to a Bring-Your-Own-Device (BYOD) model for mobile devices such as smartphones. We recognize this change as a potential threat to data privacy, both of the user and also of c...]]></description>
  <dc:date>2013-03-25</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/312/Privacy-Preserving-Distributed-Data-Mining-A-Multi-objective-Optimization-and-Algorithmic-Game-theoretic-Approach">
  <title><![CDATA[Privacy Preserving Distributed Data Mining: A Multi-objective Optimization and Algorithmic Game-theoretic Approach]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/312/Privacy-Preserving-Distributed-Data-Mining-A-Multi-objective-Optimization-and-Algorithmic-Game-theoretic-Approach</link>
  <description><![CDATA[Use of technology for data collection and analysis has seen an unprecedented growth in the last couple of decades. Individuals and organizations generate huge amount of data through everyday activities. This data is either centralized for pattern identification or mined in a distributed fashion for efficient knowledge discovery and collaborative computation. This, obviously, has raised serious concerns about privacy issues. The data mining community has responded to this challenge by deve...]]></description>
  <dc:date>2009-09-16</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/223/A-Game-Theoretic-Framework-for-Distributed-Multi-Party-Privacy-Preserving-Data-Mining">
  <title><![CDATA[A Game Theoretic Framework for Distributed Multi-Party Privacy Preserving Data Mining]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/223/A-Game-Theoretic-Framework-for-Distributed-Multi-Party-Privacy-Preserving-Data-Mining</link>
  <description><![CDATA[Privacy protection is increasingly becoming an important issue in many
data mining applications, particularly in the area of security
and surveillance. However, privacy preserving data analysis is a
non-trivial problem because of many reasons. First of all, privacy
is a social concept. In most multi-party data mining scenarios
participants have varying interests, objectives and expectations
about data privacy. Enforcing a single model of privacy with strong
assumptions regarding the be...]]></description>
  <dc:date>2007-11-19</dc:date>
 </item>
 <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/112/Online-Health-Information">
  <title><![CDATA[Online Health Information]]></title>
  <link>http://ebiquity.umbc.edu/project/html/id/112/Online-Health-Information</link>
  <description><![CDATA[The rise of social media platforms as Online Health Information Sources (OHIS) has increased the spread of health misinformation in cyberspace. The rapid dissemination of false or misleading health information, particularly in public health, can have severe consequences. Misinformation not only endangers public health but also poses significant cybersecurity risks, including eroding trust in credible sources, enabling phishing attacks, and heightening the impact of cyber threats during crises...]]></description>
  <dc:date>2024-01-13</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1221/Deontic-Policies-for-Runtime-Governance-of-Agentic-AI-Systems">
  <title><![CDATA[Deontic Policies for Runtime Governance of Agentic AI Systems]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1221/Deontic-Policies-for-Runtime-Governance-of-Agentic-AI-Systems</link>
  <description><![CDATA[Autonomous agentic AI systems driven by Large Language Models (LLMs) introduce a new class of security, privacy, and compliance challenges: an agent that can invoke tools, manipulate data, install software, and coordinate with peer agents across organizational boundaries must be constrained not just by authentication and access control, but by the full structure of enterprise governance. This includes specifying what agents are permitted and prohibited from doing, what they are obliged to do ...]]></description>
  <dc:date>2026-07-13</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1200/Automating-IoT-Data-Privacy-Compliance-by-Integrating-Knowledge-Graphs-With-Large-Language-Models">
  <title><![CDATA[Automating IoT Data Privacy Compliance by Integrating Knowledge Graphs With Large Language Models]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1200/Automating-IoT-Data-Privacy-Compliance-by-Integrating-Knowledge-Graphs-With-Large-Language-Models</link>
  <description><![CDATA[Regulatory compliance is mandatory for Internet of Things (IoT) manufacturers, particularly under stringent frameworks such as the General Data Protection Regulation (GDPR), which governs the handling of personal data. We introduce a novel framework for automating IoT compliance verification by integrating a Large Language Model (LLM) with a domain-specific Knowledge Graph (KG). The framework achieves two primary objectives: 1) leveraging the LLM to interpret natural-language compliance queri...]]></description>
  <dc:date>2025-07-25</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1179/KiNETGAN-Enabling-Distributed-Network-Intrusion-Detection-through-Knowledge-Infused-Synthetic-Data-Generation">
  <title><![CDATA[KiNETGAN: Enabling Distributed Network Intrusion Detection through Knowledge-Infused Synthetic Data Generation]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1179/KiNETGAN-Enabling-Distributed-Network-Intrusion-Detection-through-Knowledge-Infused-Synthetic-Data-Generation</link>
  <description><![CDATA[In the realm of IoT/CPS systems connected over mobile networks, traditional intrusion detection methods analyze network traffic across multiple devices using anomaly detection techniques to flag potential security threats. However, these methods face significant privacy challenges, particularly with deep packet inspection and network communication analysis. This type of monitoring is highly intrusive, as it involves examining the content of data packets, which can include personal and sensiti...]]></description>
  <dc:date>2024-05-26</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1128/Secure-and-Privacy-Compliant-Data-Sharing-An-Essential-Framework-for-Healthcare-Organizations">
  <title><![CDATA[Secure and Privacy-Compliant Data Sharing: An Essential Framework for Healthcare  Organizations]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1128/Secure-and-Privacy-Compliant-Data-Sharing-An-Essential-Framework-for-Healthcare-Organizations</link>
  <description><![CDATA[Data integration from multiple sources can improve decision-making and predict epidemiological trends. While there are many ben-
eőts to data integration, there are also privacy concerns, especially in healthcare. The Health Insurance Portability and Accountability Act
(HIPAA) is one of the essential regulations in healthcare, and it sets strict standards for the privacy and security of patient data. Often, data integration can be complex because different rules apply to different companie...]]></description>
  <dc:date>2024-01-04</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1156/Privacy-Preserving-Data-Sharing-in-Agriculture-Enforcing-Policy-Rules-for-Secure-and-Confidential-Data-Synthesis">
  <title><![CDATA[Privacy-Preserving Data Sharing in Agriculture: Enforcing Policy Rules for Secure and Confidential Data Synthesis]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1156/Privacy-Preserving-Data-Sharing-in-Agriculture-Enforcing-Policy-Rules-for-Secure-and-Confidential-Data-Synthesis</link>
  <description><![CDATA[Big Data empowers the farming community with the information needed to optimize resource usage, increase productivity, and enhance the sustainability of agricultural practices. The use of Big Data in farming requires the collection and analysis of data from various sources such as sensors, satellites, and farmer surveys. While Big Data can provide the farming community with valuable insights and improve efficiency, there is significant concern regarding the security of this data as well as th...]]></description>
  <dc:date>2023-12-18</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1127/IoT-Reg-A-Comprehensive-Knowledge-Graph-for-Real-Time-IoT-Data-Privacy-Compliance">
  <title><![CDATA[IoT-Reg: A Comprehensive Knowledge Graph for Real-Time IoT Data Privacy Compliance]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1127/IoT-Reg-A-Comprehensive-Knowledge-Graph-for-Real-Time-IoT-Data-Privacy-Compliance</link>
  <description><![CDATA[The proliferation of the Internet of Things (IoT) has led to an exponential increase in data generation, especially from wearable IoT devices. While this data influx offers unparalleled insights and connectivity, it also brings significant privacy and security challenges. Existing regulatory frameworks like the United States (US) National Institute of Standards and Technology Interagency or Internal Report (NISTIR) 8228, the US Health Insurance Portability and Accountability Act (HIPAA), and ...]]></description>
  <dc:date>2023-12-15</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1024/Semantically-Rich-Access-Control-in-Cloud-EHR-Systems-Based-on-MA-ABE">
  <title><![CDATA[Semantically Rich Access Control in Cloud EHR Systems Based on MA-ABE]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1024/Semantically-Rich-Access-Control-in-Cloud-EHR-Systems-Based-on-MA-ABE</link>
  <description><![CDATA[Winner of the Best Paper Award in the conferenceWith the rapid implementation of Cloud-based Electronic Health Record (EHR) systems, health providers are specifically concerned about handling data privacy on the cloud. Existing methods have either scalability issues by requiring that patients grant access to their medical data or a trust issue by having a single authority, thereby creating the problem of a single point of attack. Hence there is a need to develop an EHR system that addresses t...]]></description>
  <dc:date>2022-05-07</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/889/Automating-GDPR-Compliance-using-Policy-Integrated-Blockchain">
  <title><![CDATA[Automating GDPR Compliance using Policy Integrated Blockchain]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/889/Automating-GDPR-Compliance-using-Policy-Integrated-Blockchain</link>
  <description><![CDATA[Data protection regulations, like GDPR, mandate security controls to secure personal identifiable information (PII) of the users which they share with service providers. With the volume of shared data reaching exascale proportions, it is challenging to ensure GDPR compliance in real time. We propose a novel approach that integrates GDPR ontology with blockchain to facilitate real time automated data compliance. Our framework ensures data operation is allowed only when validated by data privac...]]></description>
  <dc:date>2020-05-26</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/858/Multi-Authority-Access-Control-in-a-Cloud-EHR-System-with-MA-ABE">
  <title><![CDATA[Multi Authority Access Control in a Cloud EHR System with MA-ABE]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/858/Multi-Authority-Access-Control-in-a-Cloud-EHR-System-with-MA-ABE</link>
  <description><![CDATA[With the rapid adoption of Cloud-based Electronic Health Record (EHR) systems, health providers are particularly concerned about managing data privacy on the cloud. Existing approaches have either a scalability bottleneck by requiring that patients approve each sharing of their medical data or a trust bottleneck by having a single authority control every access thereby creating the problem of a single point of attack.
To address both these bottlenecks, we have developed a novel framework tha...]]></description>
  <dc:date>2019-07-08</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/847/Automating-Privacy-Compliance-Using-Policy-Integrated-Blockchain">
  <title><![CDATA[Automating Privacy Compliance Using Policy Integrated Blockchain]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/847/Automating-Privacy-Compliance-Using-Policy-Integrated-Blockchain</link>
  <description><![CDATA[An essential requirement of any information management system is to protect data and
resources against breach or improper modifications, while at the same time ensuring data access to
legitimate users. Systems handling personal data are mandated to track its flow to comply with data
protection regulations. We have built a novel framework that integrates semantically rich data
privacy knowledge graph with Hyperledger Fabric blockchain technology, to develop an
automated access-control and...]]></description>
  <dc:date>2019-02-05</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/research/area/id/38/Blockchain">
  <title><![CDATA[Blockchain]]></title>
  <link>http://ebiquity.umbc.edu/research/area/id/38/Blockchain</link>
  <description><![CDATA[Projects looking at policy rich Blockchains for managing Data Privacy and Security]]></description>
  <dc:date>2026-10-05</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/370/Ontology-for-Data-Privacy-Policy">
  <title><![CDATA[Ontology for Data Privacy Policy]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/370/Ontology-for-Data-Privacy-Policy</link>
  <description><![CDATA[We have developed a detailed ontology, using semantic web language OWL, to define the range of information that should be included in the Privacy Policy documents. This ontology can be used by user communities to determine their privacy policies for using applications in the E-Commerce, Big Data and Cloud Computing domain.]]></description>
  <dc:date>2016-10-30</dc:date>
 </item>
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