Predicting pregnancy using large-scale data from a women's health tracking mobile application

Liu, Bo; Shi, Shuyang; Wu, Yongshang; Thomas, Daniel; Symul, Laura; Pierson, Emma; Leskovec, Jure

doi:10.48550/arxiv.1812.02222

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2019

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“…We are currently in the preliminary stages of a collaborative case study to apply the data capsule paradigm to enforce HIPAA in a medical study of menstrual data collected via mobile app. The goal of this study [32] and similar work [33,34] is to demonstrate the use of mobile apps to assess menstrual health and fertility. Data capsules will allow study participants to submit their sensitive data in the context of a policy which protects its use.…”

Section: Discussionmentioning

confidence: 99%

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

Wang

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Somani

et al. 2019

Lecture Notes in Computer Science

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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, . 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.

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Section: Discussionmentioning

confidence: 99%