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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=denial+of+service">
  <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=denial+of+service]]></link>
  <description><![CDATA[UMBC ebiquity RSS Tag Search for denial of service]]></description>
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      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1118/Bewitching-the-Battlefield-Repurposing-the-MouseJack-Attack-for-Crazyflie-Drones"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/944/Cyber-Attacks-on-Smart-Farming-Infrastructure"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/873/Extracting-Rich-Semantic-Information-about-Cybersecurity-Events"/>
      <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/355/Annotations-of-Cybersecurity-blogs-and-articles"/>
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 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1118/Bewitching-the-Battlefield-Repurposing-the-MouseJack-Attack-for-Crazyflie-Drones">
  <title><![CDATA[Bewitching the Battlefield: Repurposing the MouseJack Attack for Crazyflie Drones]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1118/Bewitching-the-Battlefield-Repurposing-the-MouseJack-Attack-for-Crazyflie-Drones</link>
  <description><![CDATA[The Internet of Battlefield Things (IoBT) connects autonomous, uncrewed air and ground vehicles with wireless networks. It is a promising technology that has the potential to significantly enhance the operational effectiveness of military units by providing them with real-time information about the battlefield and enhancing their situational awareness. Autonomous assets such as drones and sensors can gather data from various sources and transmit it back to the command center, where it can be ...]]></description>
  <dc:date>2023-05-20</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/944/Cyber-Attacks-on-Smart-Farming-Infrastructure">
  <title><![CDATA[Cyber Attacks on Smart Farming Infrastructure]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/944/Cyber-Attacks-on-Smart-Farming-Infrastructure</link>
  <description><![CDATA[Smart farming also known as precision agriculture is gaining more traction for its promising potential to fulfill increasing global food demand and supply. In a smart farm, technologies and connected devices are used in a variety of ways, from finding the real-time status of crops and soil moisture content to deploying drones to assist with tasks such as applying pesticide spray. However, the use of heterogeneous internet-connected devices has introduced numerous vulnerabilities within the sm...]]></description>
  <dc:date>2020-10-15</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/873/Extracting-Rich-Semantic-Information-about-Cybersecurity-Events">
  <title><![CDATA[Extracting Rich Semantic Information about Cybersecurity Events]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/873/Extracting-Rich-Semantic-Information-about-Cybersecurity-Events</link>
  <description><![CDATA[Articles about cybersecurity events like data breaches and ransomware attacks are common, both in general news and technical sources.  Automatically extracting structured information from these can provide valuable information to inform both human analysts and computer systems. In this paper we describe how cybersecurity events can be described via semantic schemas, examined through an initial set of five event types. Using a collection of 1,000 news articles annotated with these event types,...]]></description>
  <dc:date>2019-12-12</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/355/Annotations-of-Cybersecurity-blogs-and-articles">
  <title><![CDATA[Annotations of Cybersecurity blogs and articles]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/355/Annotations-of-Cybersecurity-blogs-and-articles</link>
  <description><![CDATA[This data is the result of a Master Thesis Project by Ravendar Lal under the supervision of Dr. Tim Finin. This dataset can be used for training technical systems. This dataset consists of manually data for cybersecurity domain where this data collection has the articles from CVES, Adobe Security Bulletins, Microsoft Security Bulletins and various blog posts. Total data has over 45,000 tokens and 5,000 tagged entities. Annotation was done by the Graduate Students of Computer Science Departmen...]]></description>
  <dc:date>2013-05-30</dc:date>
 </item>
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