Privacy: Researchers at MIT Developing System That Allows Users to Pick and Choose the Data They Share on Web, Apps

Say hello to OPENpds and SafeAnswers!
From MIT News:

…a host of recent studies have demonstrated that it’s shockingly easy to identify unnamed individuals in supposedly “anonymized” data sets, even ones containing millions of records. So, if we want the benefits of data mining — like personalized recommendations or localized services — how can we protect our privacy?
In the latest issue of PLOS One, MIT researchers offer one possible answer. Their prototype system, openPDS — short for personal data store — stores data from your digital devices in a single location that you specify: It could be an encrypted server in the cloud, but it could also be a computer in a locked box under your desk. Any cellphone app, online service, or big-data research team that wants to use your data has to query your data store, which returns only as much information as is required.
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“The example I like to use is personalized music,” says Yves-Alexandre de Montjoye, a graduate student in media arts and sciences and first author on the new paper. “Pandora, for example, comes down to this thing that they call the music genome, which contains a summary of your musical tastes. To recommend a song, all you need is the last 10 songs you listened to — just to make sure you don’t keep recommending the same one again — and this music genome. You don’t need the list of all the songs you’ve been listening to.”
With openPDS, de Montjoye says, “You share code; you don’t share data. Instead of you sending data to Pandora, for Pandora to define what your musical preferences are, it’s Pandora sending a piece of code to you for you to define your musical preferences and send it back to them.”
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“OpenPDS is one of the key enabling technologies for the digital society, because it allows users to control their data and at the same time open up its potential both at the economic level and at the level of society,” says Dirk Helbing, a professor of sociology at ETH Zurich. “I don’t see another way of making big data compatible with constitutional rights and human rights.”

Full Text PLOS One Article

“openPDS: Protecting the Privacy of Metadata through SafeAnswers”

Authors

Yves-Alexandre de Montjoye
Erez Shmueli
Samuel S. Wang
Alex Sandy Pentland

Source

PLOS One
July 09, 2014

Abstract

The rise of smartphones and web services made possible the large-scale collection of personal metadata. Information about individuals’ location, phone call logs, or web-searches, is collected and used intensively by organizations and big data researchers. Metadata has however yet to realize its full potential. Privacy and legal concerns, as well as the lack of technical solutions for personal metadata management is preventing metadata from being shared and reconciled under the control of the individual. This lack of access and control is furthermore fueling growing concerns, as it prevents individuals from understanding and managing the risks associated with the collection and use of their data. Our contribution is two-fold: (1) we describe openPDS, a personal metadata management framework that allows individuals to collect, store, and give fine-grained access to their metadata to third parties. It has been implemented in two field studies; (2) we introduce and analyze SafeAnswers, a new and practical way of protecting the privacy of metadata at an individual level. SafeAnswers turns a hard anonymization problem into a more tractable security one. It allows services to ask questions whose answers are calculated against the metadata instead of trying to anonymize individuals’ metadata. The dimensionality of the data shared with the services is reduced from high-dimensional metadata to low-dimensional answers that are less likely to be re-identifiable and to contain sensitive information. These answers can then be directly shared individually or in aggregate. openPDS and SafeAnswers provide a new way of dynamically protecting personal metadata, thereby supporting the creation of smart data-driven services and data science research.

Direct to Full Text

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