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  <event:Event rdf:about="http://ebiquity.umbc.edu/event/html/id/299/Outlier-Detection-in-Ad-Hoc-Networks-Using-Dempster-Shafer-Theory">
    <rdfs:label><![CDATA[Outlier Detection in Ad Hoc Networks Using Dempster-Shafer Theory]]></rdfs:label>
    <event:title><![CDATA[Outlier Detection in Ad Hoc Networks Using Dempster-Shafer Theory]]></event:title>
    <event:speaker><person:PhDStudent rdf:about="http://ebiquity.umbc.edu/person/html/Wenjia/Li/"><person:name><![CDATA[Wenjia  Li]]></person:name><rdfs:label><![CDATA[Wenjia  Li]]></rdfs:label></person:PhDStudent></event:speaker>
    <event:startDate rdf:datatype="&xsd;dateTime">2009-05-06T10:00:00-05:00</event:startDate>
    <event:endDate rdf:datatype="&xsd;dateTime">2009-05-06T11:30:00-05:00</event:endDate>
    <event:location><![CDATA[325b ITE]]></event:location>
    <event:abstract><![CDATA[
Mobile Ad-hoc NETworks (MANETs) are known to be vulnerable to a variety of
attacks due to lack of central authority or fixed network infrastructure.
Many security schemes have been proposed to identify misbehaving nodes.
Most of these security schemes rely on either a predefined threshold, or a
set of well-defined training data to build up the detection mechanism
before effectively identifying the malicious peers. However, it is
generally difficult to set appropriate thresholds, and collecting training
datasets representative of an attack ahead of time is also problematic. We
observe that the malicious peers generally demonstrate behavioral patterns
different from all the other normal peers, and argue that outlier
detection techniques can be used to detect malicious peers in ad hoc
networks. A problem with this approach is combining evidence from
potentially untrustworthy peers to detect the outliers. In this paper, an
outlier detection algorithm is proposed that applies the Dempster-Shafer
theory to combine observation results from multiple nodes because it can
appropriately reflect uncertainty as well as unreliability of the
observations. The simulation results show that the proposed scheme is
highly resilient to attackers and it can converge stably to a common
outlier view amongst distributed nodes with a limited communication
overhead.
]]></event:abstract>
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    <event:tag><![CDATA[manet]]></event:tag>
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