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 <channel rdf:about="http://ebiquity.umbc.edu//tags/html/?t=rif">
  <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=rif]]></link>
  <description><![CDATA[UMBC ebiquity RSS Tag Search for rif]]></description>
  <items>
    <rdf:Seq>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/441/An-architecture-for-enterprise-information-interoperability"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/433/Identification-of-common-best-practices-in-Stem-Cell-Preparation"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/428/Detecting-Comprised-Nodes-in-Wireless-Sensor-Networks"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/427/High-Resolution-Decadal-Gridding-of-NASA-Atmospheric-Infrared-Sounder-AIRS-Earth-Monitoring-Instrument-"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/339/Trust-and-Reputation-in-Social-Networks"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/275/Feature-Engineering-for-Sentiment"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/265/Mining-Social-Media-Communities-and-Content"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/264/An-Efficient-Method-for-Probabilistic-Knowledge-Integration"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/239/Using-semantic-policies-to-manage-border-gateway-route-exchanges"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/212/Detecting-Spam-Blogs-An-Adaptive-Online-Approach-"/>
      <rdf:li resource="http://ebiquity.umbc.edu/project/html/id/50/IDE-for-Rei-Policy-Language"/>
      <rdf:li resource="http://ebiquity.umbc.edu/project/html/id/16/MagicWeaver-An-Agent-Based-Simulation-Framework-For-Wireless-Sensor-Networks"/>
      <rdf:li resource="http://ebiquity.umbc.edu/project/html/id/26/Ontology-Editor-for-Eclipse"/>
      <rdf:li resource="http://ebiquity.umbc.edu/project/html/id/78/Policy-based-Automated-WAN-Configuration-and-Management"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1222/Ontology-Driven-Agentic-System-for-Automating-Security-Compliance-in-Medical-Cyber-Physical-WBANs"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1217/Deontic-Knowledge-Graphs-for-Privacy-Compliance-in-Multimodal-Disaster-Data-Sharing"/>
      <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/1193/Real-Time-Detection-of-Online-Health-Misinformation-using-an-Integrated-Knowledgegraph-LLM-Approach"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1173/GenAIPABench-A-Benchmark-for-Generative-AI-based-Privacy-Assistants"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1176/Exploring-the-Impact-of-Increased-Health-Information-Accessibility-in-Cyberspace-on-Trust-and-Self-care-Practices"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1064/A-General-Framework-for-Auditing-Differentially-Private-Machine-Learning"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1009/Cybersecurity-Knowledge-Graph-Improvement-with-Graph-Neural-Networks"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/960/Using-Knowledge-Graphs-and-Reinforcement-Learning-for-Malware-Analysis"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/945/Knowledge-Enrichment-by-Fusing-Representations-for-Malware-Threat-Intelligence-and-Behavior"/>
      <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/374/Structural-Metadata-from-ArXiv-Articles"/>
      <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/293/Trust-and-Reputation-in-Social-Networks"/>
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 </channel>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/441/An-architecture-for-enterprise-information-interoperability">
  <title><![CDATA[An architecture for enterprise information interoperability]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/441/An-architecture-for-enterprise-information-interoperability</link>
  <description><![CDATA[The World Wide Web differed from other early hypertext systems in the removal of "back links" (the ability of a hyperlinked object to link back to a referring resource). The removal of back links allowed the scalability inherent in the Web's design, but sacrificed the knowledge necessary to update links when content moved. Persistent URLs (PURLs) have been used on the Web since 1995 to provide an inexpensive and partial solution to link updates via HTTP redirection: PURLs do not change thei...]]></description>
  <dc:date>2012-11-09</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/433/Identification-of-common-best-practices-in-Stem-Cell-Preparation">
  <title><![CDATA[Identification of common best practices in Stem Cell Preparation]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/433/Identification-of-common-best-practices-in-Stem-Cell-Preparation</link>
  <description><![CDATA[Stem Cells are characterized by their ability to differentiate into specialized cells and are widely used to treat leukemia. The standard steps in Stem Cell Preparation include Isolation of Stem Cell from bone marrow or iliac crest etc. of donor, which itself could be human or mice; followed by preliminary treatment which includes centrifugation or sterilization. Specific cultures are then maintained for growth and expansion of extracted Stem Cells.


The aim of this project is to identi...]]></description>
  <dc:date>2012-04-05</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/428/Detecting-Comprised-Nodes-in-Wireless-Sensor-Networks">
  <title><![CDATA[Detecting Comprised Nodes in Wireless Sensor Networks]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/428/Detecting-Comprised-Nodes-in-Wireless-Sensor-Networks</link>
  <description><![CDATA[This week's ebiquity lab meeting will comprise of presentation by Ebiquity student, Lisa Matthews.


Lisa will talk on - Detecting Comprised Nodes in Wireless Sensor Networks



While wireless sensor networks are proving to be a versatile tool,
many of the applications in which they are implemented have sensitive
data. In other words, security is crucial in many of these
applications. Once a sensor node has been compromised, the security of
the network degrades quickly if there are...]]></description>
  <dc:date>2012-03-08</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/427/High-Resolution-Decadal-Gridding-of-NASA-Atmospheric-Infrared-Sounder-AIRS-Earth-Monitoring-Instrument-">
  <title><![CDATA[High Resolution Decadal Gridding of NASA Atmospheric Infrared Sounder (AIRS) Earth Monitoring Instrument.]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/427/High-Resolution-Decadal-Gridding-of-NASA-Atmospheric-Infrared-Sounder-AIRS-Earth-Monitoring-Instrument-</link>
  <description><![CDATA[This week's ebiquity lab meeting will comprise of presentation by PhD candidate, David Chapman.


David will talk on - High Resolution Decadal Gridding of the NASA Atmospheric Infrared Sounder (AIRS) Earth Monitoring Instrument.



Abstract: 
The NASA Atmospheric Infrared Sounder (AIRS) has been monitoring sun synchronous hyperspectral infrared radiation from Earth's surface and atmosphere operationally since September 2002, making AIRS one of the longest running IR sounders. AIRS has...]]></description>
  <dc:date>2012-03-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/339/Trust-and-Reputation-in-Social-Networks">
  <title><![CDATA[Trust and Reputation in Social Networks]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/339/Trust-and-Reputation-in-Social-Networks</link>
  <description><![CDATA[Trust is a statement (or prediction of reliance) about what is otherwise unknown or uncertain -- for example, because it is far away, cannot be verified, or is in the future. Trust is pervasive and beneficial in complex social systems. It can be built from direct interactions between the source party (truster) and the target (trustee). However, in large open systems, it is infeasible for each party to have a direct basis for trusting another party. Therefore, the participants in an open syste...]]></description>
  <dc:date>2010-03-30</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/275/Feature-Engineering-for-Sentiment">
  <title><![CDATA[Feature Engineering for Sentiment]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/275/Feature-Engineering-for-Sentiment</link>
  <description><![CDATA[Sentiment analysis upon free text is a difficult domain since
 free text is often informally written, poorly structured, and
 rife with spelling and grammatical errors. These
 characteristics make them difficult to parse and process with
 standard language analysis tools. These factors have made
 machine learning techniques such as bag of words support vector
 machines very popular. We describe a better feature space to
 use with support vector machines that relies upon the uneven
 di...]]></description>
  <dc:date>2008-11-18</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/265/Mining-Social-Media-Communities-and-Content">
  <title><![CDATA[Mining Social Media Communities and Content]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/265/Mining-Social-Media-Communities-and-Content</link>
  <description><![CDATA[Ph.D. Dissertation Defense


Social Media is changing the way we find information, share knowledge and
communicate with each other. The important factor contributing to the growth
of these technologies is the ability to easily produce "user-generated
content". Blogs, Twitter, Wikipedia, Flickr and YouTube are just a few
examples of Web 2.0 tools that are drastically changing the Internet landscape
today. These platforms allow users to produce, annotate and share information
with thei...]]></description>
  <dc:date>2008-10-16</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/264/An-Efficient-Method-for-Probabilistic-Knowledge-Integration">
  <title><![CDATA[An Efficient Method for Probabilistic Knowledge Integration]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/264/An-Efficient-Method-for-Probabilistic-Knowledge-Integration</link>
  <description><![CDATA[Probabilistic information can come from many different sources and tends to 
involve a  part  of the domain. How can we integrate the different information about probabilities, especially when they may be inconsistent?

   There are several methods dealing with this problem, such as the well
known iterative proportional fitting procedure (IPFP),
proposed by R. Kruithof in 1937 for situations that are consistent,  and the GEMA algorithm (Generalized Expectation Maximization Algorithm) giv...]]></description>
  <dc:date>2008-10-14</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/239/Using-semantic-policies-to-manage-border-gateway-route-exchanges">
  <title><![CDATA[Using semantic policies to manage border gateway route exchanges]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/239/Using-semantic-policies-to-manage-border-gateway-route-exchanges</link>
  <description><![CDATA[Policies in BGP are implemented as routing configurations that determine
how route information is shared among neighbors to control traffic flows
across networks. This process is generally template driven, device
centric, limited in its expressibility, time consuming and error prone
which can lead to configurations where policies are violated or there are
unintended consequences that are difficult to detect and resolve. In this
work, we propose an alternate mechanism for policy based ne...]]></description>
  <dc:date>2008-04-29</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/212/Detecting-Spam-Blogs-An-Adaptive-Online-Approach-">
  <title><![CDATA[Detecting Spam Blogs: An Adaptive Online Approach]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/212/Detecting-Spam-Blogs-An-Adaptive-Online-Approach-</link>
  <description><![CDATA[Weblogs, or blogs, are an important new way to publish information, engage
in discussions, and form communities on the Internet. Blogs are a global
phenomenon, and with numbers well over 100 million they form the core of
the emerging paradigm of Social Media. While the utility of blogs is
unquestionable, a serious problem now afflicts them, that of spam. Spam
blogs, or splogs are blogs with auto-generated or plagiarized content
with the sole purpose of hosting profitable contextual ads ...]]></description>
  <dc:date>2007-09-25</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/project/html/id/50/IDE-for-Rei-Policy-Language">
  <title><![CDATA[IDE for Rei Policy Language]]></title>
  <link>http://ebiquity.umbc.edu/project/html/id/50/IDE-for-Rei-Policy-Language</link>
  <description><![CDATA[Security policies define rules for access control, authentication, or authorization of entities in a system. With the increase in interest in web based e-commerce, the amount of business that is transacted on-line and the explosion in the amount of services available, the ability to
handle security and privacy is a must. Also, as computationally enabled devices (laptops, phones, PDAs, and even household appliances) become more commonplace and short range wireless connectivity improves; there...]]></description>
  <dc:date>2003-05-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/project/html/id/16/MagicWeaver-An-Agent-Based-Simulation-Framework-For-Wireless-Sensor-Networks">
  <title><![CDATA[MagicWeaver: An Agent Based Simulation Framework For Wireless Sensor Networks]]></title>
  <link>http://ebiquity.umbc.edu/project/html/id/16/MagicWeaver-An-Agent-Based-Simulation-Framework-For-Wireless-Sensor-Networks</link>
  <description><![CDATA[There is a growing interest in the research community towards a paradigm in which computing is embedded into our daily lives. Everyday objects shall act as computing devices, enriching user experience and enhancing the environments in which we live. Sensor Networks are a step in this direction. Sensor Network research is still in its infancy, with research spanning from hardware to communication to data management and to software engineering principles. To build a strong foundation on the pri...]]></description>
  <dc:date>2001-09-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/project/html/id/26/Ontology-Editor-for-Eclipse">
  <title><![CDATA[Ontology Editor for Eclipse]]></title>
  <link>http://ebiquity.umbc.edu/project/html/id/26/Ontology-Editor-for-Eclipse</link>
  <description><![CDATA[In computer science, policies are rules and
constraints that govern the behavior of software agents. The use of
policies makes systems more flexible by separating the declarative
components of the system from its implementation. Policies are usually
expressed in a readable declarative language that can be understood by
a human. Policy based security model defines rules for access control,
authorization, and authentication of software objects and entities,
and can be greatly beneficia...]]></description>
  <dc:date>2002-08-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/project/html/id/78/Policy-based-Automated-WAN-Configuration-and-Management">
  <title><![CDATA[Policy-based Automated WAN Configuration and Management]]></title>
  <link>http://ebiquity.umbc.edu/project/html/id/78/Policy-based-Automated-WAN-Configuration-and-Management</link>
  <description><![CDATA[There are many significant challenges related to configuration and management of wide-area networks due to their rapidly growing complexity, failures, and attacks.  The DARPA Knowledge Plane Study identified that main challenges to be intelligent network management, fault detection, attack response, and fast network configuration.  With uncertainty and threads of battle areas, these challenges further grow exponentially.

In order to overcome the challenges, the project aims at developing a...]]></description>
  <dc:date>2006-09-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1222/Ontology-Driven-Agentic-System-for-Automating-Security-Compliance-in-Medical-Cyber-Physical-WBANs">
  <title><![CDATA[Ontology Driven Agentic System for Automating Security Compliance in Medical Cyber-Physical WBANs]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1222/Ontology-Driven-Agentic-System-for-Automating-Security-Compliance-in-Medical-Cyber-Physical-WBANs</link>
  <description><![CDATA[Medical Wireless Body Area Networks (WBANs)
operate as medical cyber-physical systems (MCPS) that continuously
sense and transmit sensitive patient health data, creating
significant security, privacy, and regulatory challenges. Traditional
WBAN protections focus on lightweight cryptography but
lack semantic reasoning and automated compliance of data regulations
such as Health Insurance Portability and Accountability
Act (HIPAA) and General Data Protection Regulation (GDPR).
We have de...]]></description>
  <dc:date>2026-07-13</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1217/Deontic-Knowledge-Graphs-for-Privacy-Compliance-in-Multimodal-Disaster-Data-Sharing">
  <title><![CDATA[Deontic Knowledge Graphs for Privacy Compliance in Multimodal Disaster Data Sharing]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1217/Deontic-Knowledge-Graphs-for-Privacy-Compliance-in-Multimodal-Disaster-Data-Sharing</link>
  <description><![CDATA[Disaster response requires sharing heterogeneous artifacts, from tabular assistance records to UAS imagery, under overlapping privacy mandates. Operational systems often reduce compliance to binary access control, which is brittle in time-critical workflows. We present a novel deontic knowledge graph-based framework that integrates a Disaster Management Knowledge Graph (DKG) with a Policy Knowledge Graph (PKG) derived from IoT-Reg and FEMA/DHS privacy drivers. Our release decision function su...]]></description>
  <dc:date>2026-01-07</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/1193/Real-Time-Detection-of-Online-Health-Misinformation-using-an-Integrated-Knowledgegraph-LLM-Approach">
  <title><![CDATA[Real-Time Detection of Online Health Misinformation using an Integrated Knowledgegraph-LLM Approach]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1193/Real-Time-Detection-of-Online-Health-Misinformation-using-an-Integrated-Knowledgegraph-LLM-Approach</link>
  <description><![CDATA[Winner of Best Student Paper Award 
The dramatic surge of health misinformation on social media platforms poses a significant threat to public health, contributing to hesitancy in vaccines, delayed medical interventions, and the adoption of untested or harmful treatments. We present a novel, hybrid AI-driven framework designed for the real-time detection of health misinformation on social media platforms while prioritizing user privacy. The framework integrates the strengths of Large Langua...]]></description>
  <dc:date>2025-07-11</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1173/GenAIPABench-A-Benchmark-for-Generative-AI-based-Privacy-Assistants">
  <title><![CDATA[GenAIPABench: A Benchmark for Generative AI-based Privacy Assistants]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1173/GenAIPABench-A-Benchmark-for-Generative-AI-based-Privacy-Assistants</link>
  <description><![CDATA[Website privacy policies are often lengthy and intricate. Privacy assistants help simplify policies and make them more accessible and user-friendly. The emergence of generative AI (genAI) offers new opportunities to build privacy assistants that can answer users’ questions about privacy policies. However, genAI’s reliability is a concern due to its potential for producing inaccurate information. This study introduces GenAIPABench, a benchmark for evaluating Generative AI-based Privacy Ass...]]></description>
  <dc:date>2024-07-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1176/Exploring-the-Impact-of-Increased-Health-Information-Accessibility-in-Cyberspace-on-Trust-and-Self-care-Practices">
  <title><![CDATA[Exploring the Impact of Increased Health Information Accessibility in Cyberspace on Trust and Self-care Practices]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1176/Exploring-the-Impact-of-Increased-Health-Information-Accessibility-in-Cyberspace-on-Trust-and-Self-care-Practices</link>
  <description><![CDATA[More health information is in cyberspace than ever before, presenting
both opportunities and challenges for health information
seeking and self-care practices, particularly in underserved populations
who face health disparities for various reasons, including
limited healthcare access and high costs. We have investigated the
effect of increased health information accessibility in cyberspace on
self-care practices and trust in underserved populations of African
descent by surveying how i...]]></description>
  <dc:date>2024-06-21</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1064/A-General-Framework-for-Auditing-Differentially-Private-Machine-Learning">
  <title><![CDATA[A General Framework for Auditing Differentially Private Machine Learning]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1064/A-General-Framework-for-Auditing-Differentially-Private-Machine-Learning</link>
  <description><![CDATA[We present a framework to statistically audit the privacy guarantee conferred by a differentially private machine learner in practice. While previous works have taken steps toward evaluating privacy loss through poisoning attacks or membership inference, they have been tailored to specific models or have demonstrated low statistical power. Our work develops a general methodology to empirically evaluate the privacy of differentially private machine learning implementations, combining improved ...]]></description>
  <dc:date>2022-11-28</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1009/Cybersecurity-Knowledge-Graph-Improvement-with-Graph-Neural-Networks">
  <title><![CDATA[Cybersecurity Knowledge Graph Improvement with Graph Neural Networks]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1009/Cybersecurity-Knowledge-Graph-Improvement-with-Graph-Neural-Networks</link>
  <description><![CDATA[Cybersecurity Knowledge Graphs (CKGs) help in
aggregating information about cyber-events. CKGs combined
with reasoning and querying systems such as SPARQL enable
security researchers to look up information about past cyberevents
that is helpful in understanding future cyber-events or
drawing similarity with a known cyber-event recorded in a
CKG. CKGs have assertions in the form of semantic triples. The
triples describe a relationship between a subject and object, both
of which are cyb...]]></description>
  <dc:date>2021-12-15</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/960/Using-Knowledge-Graphs-and-Reinforcement-Learning-for-Malware-Analysis">
  <title><![CDATA[Using Knowledge Graphs and Reinforcement Learning for Malware Analysis]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/960/Using-Knowledge-Graphs-and-Reinforcement-Learning-for-Malware-Analysis</link>
  <description><![CDATA[Machine learning algorithms used to detect attacks are limited by the fact that they cannot incorporate the background knowledge that an analyst has. This limits their suitability in detecting new attacks. Reinforcement learning is different from traditional machine learning algorithms used in the cybersecurity domain. Compared to traditional ML algorithms, reinforcement learning does not need a mapping of the input-output space or a specific user-defined metric to compare data points. This i...]]></description>
  <dc:date>2020-12-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/945/Knowledge-Enrichment-by-Fusing-Representations-for-Malware-Threat-Intelligence-and-Behavior">
  <title><![CDATA[Knowledge Enrichment by Fusing Representations for Malware Threat Intelligence and Behavior]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/945/Knowledge-Enrichment-by-Fusing-Representations-for-Malware-Threat-Intelligence-and-Behavior</link>
  <description><![CDATA[Security engineers and researchers use their disparate knowledge and discretion to identify malware present in a system. Sometimes, they may also use previously extracted knowledge and available Cyber Threat Intelligence (CTI) about known attacks to establish a pattern. To aid in this process, they need knowledge about malware behavior mapped to available CTI. Such mappings enrich our CKG and also help verify the information. In this paper, we retrieve malware samples and execute them in a lo...]]></description>
  <dc:date>2020-11-15</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/374/Structural-Metadata-from-ArXiv-Articles">
  <title><![CDATA[Structural Metadata from ArXiv Articles]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/374/Structural-Metadata-from-ArXiv-Articles</link>
  <description><![CDATA[{
  "@context": "http://schema.org/",
  "@type": "Dataset",
  "name": "Structural Metadata from ArXiv Articles",
  "version": "1.0",
  "license": "https://creativecommons.org/licenses/by-sa/4.0/",
  "description": "The dataset contains metadata encoded in JSON and extracted from more than one million arXiv articles that were put online before the end of 2016. The metadata includes the arXiv id, category names, title, author names, abstract, link to article, publication date and table ...]]></description>
  <dc:date>2017-09-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/293/Trust-and-Reputation-in-Social-Networks">
  <title><![CDATA[Trust and Reputation in Social Networks]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/293/Trust-and-Reputation-in-Social-Networks</link>
  <description><![CDATA[Trust is a statement (or prediction of reliance) about what is otherwise
unknown or uncertain -- for example, because it is far away, cannot be
verified, or is in the future. Trust is pervasive and beneficial in complex
social systems. It can be built from direct interactions between the source
party (truster) and the target (trustee). However, in large open systems, it
is infeasible for each party to have a direct basis for trusting another
party. Therefore, the participants in an open...]]></description>
  <dc:date>2010-03-30</dc:date>
 </item>
</rdf:RDF>
