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      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/999/CyBERT-Contextualized-Embeddings-for-the-Cybersecurity-Domain"/>
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 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/999/CyBERT-Contextualized-Embeddings-for-the-Cybersecurity-Domain">
  <title><![CDATA[CyBERT: Contextualized Embeddings for the Cybersecurity Domain]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/999/CyBERT-Contextualized-Embeddings-for-the-Cybersecurity-Domain</link>
  <description><![CDATA[We present CyBERT, a domain-specific Bidirectional Encoder Representations from Transformers (BERT) model, fine-tuned with a large corpus of textual cybersecurity data. State-of-the-art natural language models that can process dense, fine-grained textual threat, attack, and vulnerability information can provide numerous benefits to the cybersecurity community. The primary contribution of this paper is to provide the security community with an initial fine-tuned BERT model that can perform a v...]]></description>
  <dc:date>2021-12-15</dc:date>
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 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/752/CyberTwitter-Using-Twitter-to-generate-alerts-for-Cybersecurity-Threats-and-Vulnerabilities">
  <title><![CDATA[CyberTwitter: Using Twitter to generate alerts for Cybersecurity Threats and Vulnerabilities]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/752/CyberTwitter-Using-Twitter-to-generate-alerts-for-Cybersecurity-Threats-and-Vulnerabilities</link>
  <description><![CDATA[In order to secure vital personal and organizational systems, we require timely intelligence on cybersecurity threats and vulnerabilities. Intelligence about these threats is generally available in both overt and covert sources, like the National Vulnerability Database, CERT alerts, blog posts, social media, and dark web resources. Intelligence updates about cybersecurity can be viewed as temporal events that a security analyst must keep up with so as to secure a computer system. We describe ...]]></description>
  <dc:date>2016-08-19</dc:date>
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