Data Capsule: A New Paradigm for Automatic Compliance with Data Privacy Regulations View Full Text


Ontology type: schema:Chapter      Open Access: True


Chapter Info

DATE

2019-10-23

AUTHORS

Lun Wang , Joseph P. Near , Neel Somani , Peng Gao , Andrew Low , David Dao , Dawn Song

ABSTRACT

The increasing pace of data collection has led to increasing awareness of privacy risks, resulting in new data privacy regulations like General data Protection Regulation (GDPR). Such regulations are an important step, but automatic compliance checking is challenging. In this work, we present a new paradigm, Data Capsule, for automatic compliance checking of data privacy regulations in heterogeneous data processing infrastructures. Our key insight is to pair up a data subject’s data with a policy governing how the data is processed. Specified in our formal policy language: PrivPolicy, the policy is created and provided by the data subject alongside the data, and is associated with the data throughout the life-cycle of data processing (e.g., data transformation by data processing systems, data aggregation of multiple data subjects’ data). We introduce a solution for static enforcement of privacy policies based on the concept of residual policies, and present a novel algorithm based on abstract interpretation for deriving residual policies in PrivPolicy. Our solution ensures compliance automatically, and is designed for deployment alongside existing infrastructure. We also design and develop PrivGuard, a reference data capsule manager that implements all the functionalities of Data Capsule paradigm . More... »

PAGES

3-23

Book

TITLE

Heterogeneous Data Management, Polystores, and Analytics for Healthcare

ISBN

978-3-030-33751-3
978-3-030-33752-0

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-030-33752-0_1

DOI

http://dx.doi.org/10.1007/978-3-030-33752-0_1

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1122094426


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