openPDS: Protecting the Privacy of Metadata through SafeAnswers
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...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | en_US |
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Public Library of Science
2014
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| Online Access: | http://hdl.handle.net/1721.1/88264 https://orcid.org/0000-0002-8053-9983 https://orcid.org/0000-0002-0346-2994 https://orcid.org/0000-0001-9086-589X |
| _version_ | 1811087915028054016 |
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| author | de Montjoye, Yves-Alexandre Shmueli, Erez Wang, Samuel S. Pentland, Alex Paul |
| author2 | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory |
| author_facet | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory de Montjoye, Yves-Alexandre Shmueli, Erez Wang, Samuel S. Pentland, Alex Paul |
| author_sort | de Montjoye, Yves-Alexandre |
| collection | MIT |
| description | 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. |
| first_indexed | 2024-09-23T13:53:37Z |
| format | Article |
| id | mit-1721.1/88264 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T13:53:37Z |
| publishDate | 2014 |
| publisher | Public Library of Science |
| record_format | dspace |
| spelling | mit-1721.1/882642022-10-01T17:49:51Z openPDS: Protecting the Privacy of Metadata through SafeAnswers de Montjoye, Yves-Alexandre Shmueli, Erez Wang, Samuel S. Pentland, Alex Paul Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology. Media Laboratory Program in Media Arts and Sciences (Massachusetts Institute of Technology) de Montjoye, Yves-Alexandre Shmueli, Erez Wang, Samuel S. Pentland, Alex Paul 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. U.S. Army Research Laboratory (Cooperative Agreement W911NF-09-2-0053) Center for Complex Engineering Systems MIT Media Lab Consortium 2014-07-11T13:21:16Z 2014-07-11T13:21:16Z 2014-07 2014-03 Article http://purl.org/eprint/type/JournalArticle 1932-6203 http://hdl.handle.net/1721.1/88264 de Montjoye, Yves-Alexandre, Erez Shmueli, Samuel S. Wang, and Alex Paul Pentland. https://orcid.org/0000-0002-8053-9983 https://orcid.org/0000-0002-0346-2994 https://orcid.org/0000-0001-9086-589X en_US http://dx.doi.org/10.1371/journal.pone.0098790 PLoS ONE Creative Commons Attribution http://creativecommons.org/licenses/by/4.0/ application/pdf Public Library of Science PLoS |
| spellingShingle | de Montjoye, Yves-Alexandre Shmueli, Erez Wang, Samuel S. Pentland, Alex Paul openPDS: Protecting the Privacy of Metadata through SafeAnswers |
| title | openPDS: Protecting the Privacy of Metadata through SafeAnswers |
| title_full | openPDS: Protecting the Privacy of Metadata through SafeAnswers |
| title_fullStr | openPDS: Protecting the Privacy of Metadata through SafeAnswers |
| title_full_unstemmed | openPDS: Protecting the Privacy of Metadata through SafeAnswers |
| title_short | openPDS: Protecting the Privacy of Metadata through SafeAnswers |
| title_sort | openpds protecting the privacy of metadata through safeanswers |
| url | http://hdl.handle.net/1721.1/88264 https://orcid.org/0000-0002-8053-9983 https://orcid.org/0000-0002-0346-2994 https://orcid.org/0000-0001-9086-589X |
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