<html><head><style type='text/css'>p { margin: 0; }</style></head><body><div style='font-family: arial,helvetica,sans-serif; font-size: 12pt; color: #000000'><div style="color:#000;font-weight:normal;font-style:normal;text-decoration:none;font-family:Helvetica,Arial,sans-serif;font-size:12pt;"><style>p { margin: 0; }</style><div style="font-family: arial,helvetica,sans-serif; font-size: 12pt; color: #000000"><b>Data Privacy Technologies: >From Alchemy to an Engineering Discipline</b>
<br>
<b><a href="http://randomwalker.info/" target="_blank">Arvind Narayanan</a></b>, <a href="http://stanford.edu/" target="_blank">Stanford University</a>
<br>
<b><a name="2012-03-08">Thursday, March 8, 2012</a>, 4:30 PM<br>Computer Science Small Auditorium (Room 105)<br><br></b>
Established practices for data privacy focus on simplistic
transformations such as the removal of “personally identifiable
information.” On the other hand, academia has produced a long line of
work on privacy-preserving computation that has yet to be translated
into practice. I envision privacy technologies as an engineering
discipline grounded in a solid understanding of what technological
mechanisms can and cannot do.<br><br><p>
In this talk I will describe my past, ongoing and planned work towards
this goal. The first part of this research program — and the main topic
of my doctoral work — has been to demonstrate the inadequacy of the
current paradigm by developing reidentification and statistical
inference algorithms for various types of “anonymized” data: our
preferences, transactions, social relationships, and behavior. The
second part is to develop an approach to building systems based on
lightweight cryptography, a hybrid of centralized and decentralized
architectures, and incorporation of policy-based defenses. I will
describe how I have applied these principles to my work on location
privacy and behavioral ad targeting. <br></p><p><br></p>
Arvind Narayanan is a post-doctoral computer science researcher at
Stanford and a junior affiliate scholar at the Stanford Law School
Center for Internet and Society. He completed his Ph.D at UT Austin in
2009. Narayanan studies information privacy and security, and moonlights
in policy. His paper on deanonymization of large datasets won the 2008
Privacy Enhancing Technologies award and his 2011 paper on location
privacy at NDSS won the distinguished paper award.
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