3,797 research outputs found
XRay: Enhancing the Web's Transparency with Differential Correlation
Today's Web services - such as Google, Amazon, and Facebook - leverage user
data for varied purposes, including personalizing recommendations, targeting
advertisements, and adjusting prices. At present, users have little insight
into how their data is being used. Hence, they cannot make informed choices
about the services they choose. To increase transparency, we developed XRay,
the first fine-grained, robust, and scalable personal data tracking system for
the Web. XRay predicts which data in an arbitrary Web account (such as emails,
searches, or viewed products) is being used to target which outputs (such as
ads, recommended products, or prices). XRay's core functions are service
agnostic and easy to instantiate for new services, and they can track data
within and across services. To make predictions independent of the audited
service, XRay relies on the following insight: by comparing outputs from
different accounts with similar, but not identical, subsets of data, one can
pinpoint targeting through correlation. We show both theoretically, and through
experiments on Gmail, Amazon, and YouTube, that XRay achieves high precision
and recall by correlating data from a surprisingly small number of extra
accounts.Comment: Extended version of a paper presented at the 23rd USENIX Security
Symposium (USENIX Security 14
Research and Education in Computational Science and Engineering
Over the past two decades the field of computational science and engineering
(CSE) has penetrated both basic and applied research in academia, industry, and
laboratories to advance discovery, optimize systems, support decision-makers,
and educate the scientific and engineering workforce. Informed by centuries of
theory and experiment, CSE performs computational experiments to answer
questions that neither theory nor experiment alone is equipped to answer. CSE
provides scientists and engineers of all persuasions with algorithmic
inventions and software systems that transcend disciplines and scales. Carried
on a wave of digital technology, CSE brings the power of parallelism to bear on
troves of data. Mathematics-based advanced computing has become a prevalent
means of discovery and innovation in essentially all areas of science,
engineering, technology, and society; and the CSE community is at the core of
this transformation. However, a combination of disruptive
developments---including the architectural complexity of extreme-scale
computing, the data revolution that engulfs the planet, and the specialization
required to follow the applications to new frontiers---is redefining the scope
and reach of the CSE endeavor. This report describes the rapid expansion of CSE
and the challenges to sustaining its bold advances. The report also presents
strategies and directions for CSE research and education for the next decade.Comment: Major revision, to appear in SIAM Revie
HathiTrust Research Center: Computational Research on the HathiTrust Repository
PIs (exec mgt team): Beth A. Plale, Indiana University; Marshall Scott Poole, University of Illinois
Urbana-Champaign ; Robert McDonald, IU; John Unsworth (UIUC) Senior investigators: Loretta
Auvil (UIUC); Johan Bollen (IU), Randy Butler (UIUC); Dennis Cromwell (IU), Geoffrey Fox (IU),
Eileen Julien (IU), Stacy Kowalczyk (IU); Danny Powell (UIUC); Beth Sandore (UIUC); Craig
Stewart (IU); John Towns (UIUC); Carolyn Walters (IU), Michael Welge (UIUC); Eric Wernert
(IU
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