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  <title><![CDATA[Ph.D. Proposal Oral Exam - Xiaojing Liao]]></title>
  <body><![CDATA[<p><strong>Title:&nbsp; </strong><em>Evaluation Security Risks and Cyber Intelligence of Promotional Infection Attack</em></p>

<p><strong>Committee:&nbsp; </strong></p>

<p>Dr. Beyah, Advisor&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</p>

<p>Dr. Owen, Chair</p>

<p>Dr. Copeland</p>

<p><strong>Abstract: </strong></p>

<p>The objective of the proposed research is to study the evolution of promotional infection attack with the newly-emergent attack techniques and platforms, and then propose highly efficient and accurate detection technique to defend against the prevalence of promotional infection attack. In particular, the proposed research characterize long-tail SEO spam on cloud web hosting services; discover and study the cloud repository as malicious service and propose an efficient promotional-Infection detection tool through semantic inconsistency search. Our measurement studies bring to light the stunning impacts of such promotional attacks, and the proposed detection technique is highly effective, incurring low false positives and negatives.</p>
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