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"><span class="Apple-style-span" style="font-family: Helvetica;
font-size: medium; ">Title: Privacy and the Mobile Revolution</span></p>
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"><span style="font-family: Helvetica; font-size: medium; ">Ramesh
Govindan</span> </p>
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"><span class="Apple-style-span" style="font-family: Helvetica;
font-size: medium; ">Professor, </span><span
class="Apple-style-span" style="font-family: Helvetica;
font-size: medium; ">Computer Science Department, </span><span
class="Apple-style-span" style="border-collapse: separate;
font-family: Helvetica; border-spacing: 0px; font-size:
medium; "><span class="Apple-style-span"
style="border-collapse: separate; border-spacing: 0px; ">University
of Southern California</span></span> </p>
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">Time and location: Oct 18, 2013 11:00am in 3105 EB</div>
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"><span style="font-family: Helvetica; font-size: medium; "><br>
</span></p>
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"><span style="font-family: Helvetica; font-size: medium; ">Abstract:</span></p>
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"><span style="font-family: Helvetica; font-size: medium; ">Mobile
computing has, in the past half a decade, taken off in ways</span> <span
style="font-family: Helvetica; font-size: medium; ">that were
not anticipated. An important component of this revolution </span><span
style="font-family: Helvetica; font-size: medium; ">has been
the co-evolution of cloud computing, which has been used to </span><span
style="font-family: Helvetica; font-size: medium; ">enhance
the capabilities of a mobile device. If this revolution is </span><span
style="font-family: Helvetica; font-size: medium; ">to be
sustained, it is imperative that we leverage the strengths of </span><span
style="font-family: Helvetica; font-size: medium; ">mobile
devices, namely the presence of many useful sensors, in novel </span><span
style="font-family: Helvetica; font-size: medium; ">ways that
greatly increase their utility. Sensor data (audio, images, </span><span
style="font-family: Helvetica; font-size: medium; ">video)
sharing has proven to have enormous social value, and a </span><span
style="font-family: Helvetica; font-size: medium; ">challenge
in sensor data sharing but one that provides interesting </span><span
style="font-family: Helvetica; font-size: medium; ">opportunities,
is to ensure the privacy of sensor data. In this talk, </span><span
style="font-family: Helvetica; font-size: medium; ">I will
present two pieces of recent work that suggest a common </span><span
style="font-family: Helvetica; font-size: medium; ">framework
within which to explore privacy issues for sensor data.</span></p>
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"><span class="Apple-style-span" style="border-collapse:
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Bio:<br>
</span></p>
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"><span class="Apple-style-span" style="border-collapse:
separate; font-family: Helvetica; border-spacing: 0px;
font-size: medium; ">Ramesh Govindan received his B. Tech.
degree from the Indian Institute of Technology at Madras, and
his M.S. and Ph.D. degrees from the University of California
at Berkeley. He is a Professor in the Computer Science
Department at the University of Southern California. His
research interests include routing and measurements in
large internets, wireless sensor networks, and mobile
computing systems. He is a Fellow of the ACM.</span></p>
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"><span class="Apple-style-span" style="border-collapse:
separate; font-family: Helvetica; border-spacing: 0px;
font-size: medium; ">Host: </span><span
class="Apple-style-span" style="font-family: Helvetica;
font-size: medium; ">Dr. Guoliang Xing</span></p>
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<div>-------------------------</div>
<div>Dr. Xiaoming Liu</div>
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<div>Assistant Professor</div>
<div>Department of Computer Science and Engineering</div>
<div>Michigan State University</div>
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