White Papers

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FPF and Privacy Analytics Identify “A Practical Path Toward Genetic Privacy”

Paper highlights de-identification standards, re-identification research, and emerging technical, contractual, and policy protections that can safeguard genetic data while supporting research. Genomic data is arguably the most personal of all personally identifiable information (“PII”). Techniques to de-identify genomic data to limit privacy and security risks to individuals–while that data is used for research and statistical […]

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The Future of Privacy Technology

Today, FPF is making available a report co-authored by CEO Jules Polonetsky and Policy Fellow Jeremy Greenberg that identifies future directions and requirements of privacy technology from the industry perspective. With support by the National Science Foundation under Grant No. 1939288, a survey was designed and administered to industry privacy leaders to provide input on […]

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Privacy 2020: 10 Privacy Risks and 10 Privacy Enhancing Technologies to Watch in the Next Decade

Today, FPF is publishing a white paper co-authored by CEO Jules Polonetsky and hackylawyER Founder Elizabeth Renieris to help corporate officers, nonprofit leaders, and policymakers better understand privacy risks that will grow in prominence during the 2020s, as well as rising technologies that will be used to help manage privacy through the decade. Leaders must understand […]

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A Privacy Playbook for Connected Car Data

Drivers and passengers expect cars to be safe, comfortable, and trustworthy. Individuals often consider the details of their travels—and the vehicles that take them between their home, the office, a hospital, their place of worship, or their child’s school—to be sensitive, personal data. The newest cars contain numerous sensors, from cameras and GPS to accelerometers […]

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New White Paper Provides Guidance on Embedding Data Protection Principles in Machine Learning

Immuta and the Future of Privacy Forum (FPF) today released a working white paper, Data Protection by Process: How to Operationalise Data Protection by Design for Machine Learning, that provides guidance on embedding data protection principles within the life cycle of a machine learning model.  Data Protection by Design (DPbD) is a core data protection requirement […]

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Comparing Privacy Laws: GDPR v. CCPA

In November 2018, OneTrust DataGuidance and FPF partnered to publish a guide to the key differences between the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act of 2018 (CCPA).  Since then, a series of bills, signed by the California Governor on 11 October 2019, amended the CCPA to exempt from its application […]

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FPF Report: IoT Devices Should Deal with Privacy Impacts for People with Disabilities

FPF has released The Internet of Things (IoT) and People with Disabilities: Exploring the Benefits, Challenges, and Privacy Tensions. This paper explores the nuances of privacy considerations for people with disabilities using IoT services and provides recommendations to address privacy considerations, which can include transparency, individual control, respect for context, the need for focused collection […]

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Full house at IAPP Brussels interested in Deciphering Legitimate Interests. Download our LI Report here!

The session that the Future of Privacy Forum organized for the IAPP Europe Congress in Brussels on November 28, Deciphering “legitimate interests”: actual enforcement cases and tested solutions, generated great interest among privacy professionals. We had a full house attending – more than 500 participants, according to the IAPP. The panel was based on a Report published earlier this year by the FPF and Nymity.

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CCPA, face to face with the GDPR: An in depth comparative analysis

The General Data Protection Regulation (Regulation (EU) 2016/679) (‘GDPR’) and the California Consumer Privacy Act of 2018 (‘CCPA’) both aim to guarantee strong protection for individuals regarding their personal data and apply to businesses that collect, use, or share consumer data, whether the information was obtained online or offline.