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 <channel rdf:about="http://ebiquity.umbc.edu//tags/html/?t=vanet">
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 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/153/StreetSmart-Traffic-Discovering-and-Disseminating-Automobile-Congestion-Using-VANET-s">
  <title><![CDATA[StreetSmart Traffic: Discovering and Disseminating Automobile Congestion Using VANET's]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/153/StreetSmart-Traffic-Discovering-and-Disseminating-Automobile-Congestion-Using-VANET-s</link>
  <description><![CDATA[Automobile traffic is a major problem in developed societies.  We collectively waste huge amounts of time and resources traveling through traffic congestion.  Drivers choose the route that they believe will be  the fastest; however traffic congestion can significantly change the duration of a trip.  Drivers that know the location of areas of slow traffic can choose other, more efficient routes.  We could save significant amounts of time if traffic congestion patterns could be effectively disc...]]></description>
  <dc:date>2006-05-03</dc:date>
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 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/712/SVM-CASE-An-SVM-based-Context-Aware-Security-Framework-for-Vehicular-Ad-hoc-Networks">
  <title><![CDATA[SVM-CASE: An SVM-based Context Aware Security Framework for Vehicular Ad-hoc Networks]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/712/SVM-CASE-An-SVM-based-Context-Aware-Security-Framework-for-Vehicular-Ad-hoc-Networks</link>
  <description><![CDATA[Vehicular Ad-hoc Networks (VANETs) are known to be very susceptible to various malicious attacks. To detect and mitigate these malicious attacks, many security mechanisms have been studied for VANETs. In this paper, we propose a context-aware security framework for VANETs that uses the Support Vector Machine (SVM) algorithm to automatically determine the boundary between malicious nodes and normal ones. Compared to existing security solutions for VANETs, the proposed framework is more resilie...]]></description>
  <dc:date>2015-09-06</dc:date>
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 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/354/StreetSmart-Traffic-Discovering-and-Disseminating-Automobile-Congestion-Using-VANETs">
  <title><![CDATA[StreetSmart Traffic: Discovering and Disseminating Automobile Congestion Using VANETs]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/354/StreetSmart-Traffic-Discovering-and-Disseminating-Automobile-Congestion-Using-VANETs</link>
  <description><![CDATA[Automobile traffic is a major problem in developed societies. We collectively waste huge amounts of time and resources traveling through traffic congestion. Drivers choose the route that they believe will be the fastest; however traffic congestion can significantly change the duration of a trip. Significant savings of fuel and time could be achieved if traffic congestion patterns could be effectively discovered and disseminated to drivers. We propose a system that uses a standard GPS driving ...]]></description>
  <dc:date>2007-04-22</dc:date>
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 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/350/StreetSmart-Traffic-Discovering-and-Disseminating-Automobile-Congestion-Using-VANET-s">
  <title><![CDATA[StreetSmart Traffic: Discovering and Disseminating Automobile Congestion Using VANET's]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/350/StreetSmart-Traffic-Discovering-and-Disseminating-Automobile-Congestion-Using-VANET-s</link>
  <description><![CDATA[Automobile traffic is a major problem in developed societies.  We collectively waste huge amounts of time and resources traveling through traffic congestion.  Drivers choose the route that they believe will be the fastest; however traffic congestion can significantly change the duration of a trip.  Drivers that know the location of areas of slow traffic can choose other, more efficient routes.  We could save significant amounts of time if traffic congestion patterns could be effectively disco...]]></description>
  <dc:date>2006-08-01</dc:date>
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