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This paper discusses a framework for user-controlled privacy in the context of social data access. It explores how users can specify who accesses their data and for what purposes, addressing the challenges of digital footprints and data sharing in environments such as social networks and medical records. The proposed policy-based infrastructure enables granular access control, allowing for diverse access modes from complete to abstract levels. Emphasizing the importance of user privacy and the need for privacy-preserving analysis techniques, this work aims to enhance user trust and safeguard sensitive information in an interconnected world.
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A Policy Based Infrastructurefor Social Data Accesswith Privacy Guarantees Tim Finin (UMBC) for: Palanivel Kodeswaran (UMBC) Evelyne Viegas (Microsoft Research) POLICY 2010, Fairfax VA 21 July 2010 http://ebiquity.umbc.edu/paper/html/id/493/
Connected Data • We “leave” our digital footprints online in discussion forums, social networks, web searches • Copying and sharing Data is easy • Users have no control over how their data is used and inferences that can be made based on their data
Personalization Garden Veggie with minimal cheese
Personalization? That’s not enough running!! E-mail Sub: Insurance Renewal Dear John, In reviewing your record, we have decided to increase your premium to better serve your needs and that of your family.
User Control over Private Data There is a need for a framework in which users can specify their privacy preferences in terms of who can access their data and how it can be used Sticky Policy Phone number can be used for emergency contact PhoneNumber Phone number can’t be used for marketing
Data Sharing for Scientific Research • Large amounts of Data behind closed walls • Medical data, search data, finance data • Trend continues with user generated data as well • Facebook, Health Vault • Researchers can benefit from access to this data • User trends, epidemiology models, search ranking • Most research can be performed with aggregate data • But remember the AOL fiasco
Policy Based Infrastructure We’ve describe a policy-based infrastructure that • Allows users to specify who can access what and why • Adds additional access modes for releasing data at different granularities • Extends the traditional binary semantics of access control viz. allow/deny with emerging privacy preserving analysis techniques
Complete Access Access to the complete and detailed data Health Vault Custodian & Invitee Facebook Friends Picture from [ars]
Abstract Access Access to data encoded using more general,abstract concepts, e.g., in Baltimore as opposed to at given lat-lon coordinates Financial Websites like Covester allow sharing abstract portfolio information Google Latitude for location information Picture from [gpsobsessed]
Statistical Access User trends in search data using differential privacy The number of distinct users searching over the duration of a day at different epsilon levels C. Dwork, Differential privacy, Int. Col. Automata, languages and programming, pp. 1-12, Springer, 2006.
Example Policies Alice says ?Bob can readCompleteAccess/MyHealth if ?Bob is PrimaryPhysician Alice says ?Bob can readAbstractAccess/MyFinance if ?Bob is InvestorFriend MS says ?Bob can readStatisticalAccess/SearchData if ?Bob is Researcher