PETs Use Case: Measuring Digital Literacy with Telemetry Data Using Differential Privacy
Digital literacy, loosely defined as competency with a range of digital technologies, is a key skill for full social and democratic participation, but it is a difficult thing to measure across a large population. Having accurate data about how people use technology can inform how educators, policymakers, and technology companies make decisions and are especially […]
Comparison of Privacy Enhancing Technologies (PETs)
This comparative reference chart covers seven PETs — Differential Privacy, Synthetic Data, Federated Learning, Trusted Execution Environments, Secure Multi-Party Computation, Homomorphic Encryption, and Zero-Knowledge Proofs — across six dimensions: approach, benefits, limitations, example use case, data utility impact, and implementation complexity. The chart is designed as a standalone reference for practitioners who need to quickly […]
Privacy Enhancing Technologies for EdTech Service Providers
Educational research answers questions about program effectiveness, equity, access, and long‑term outcomes. EdTech vendors typically need student-level data and enough context to ensure their research is effective and accomplishes their goal. At the same time, disclosing student data to EdTech vendors may increase the risk of reidentification. The risk is not limited to direct identifiers […]
Privacy Enhancing Technologies for Education Researchers
Educational research answers questions about program effectiveness, equity, access, and long‑term outcomes. Researchers typically need student-level data and enough context to ensure their research is effective and accomplishes their goal. At the same time, disclosing student data to researchers may increase the risk of reidentification. The risk is not limited to direct identifiers such as […]
Privacy Enhancing Technologies for State Education Agencies
This report describes the Privacy-Enhancing Technologies (PETs) most relevant to State Education Agencies (SEAs) and Statewide Longitudinal Data Systems (SLDS) environments, explains what each can and cannot do analytically and operationally, and provides use case guidance for matching PET selection to specific workflows. PETs complement rather than replace strong governance — data minimization, least-privilege access, […]
Privacy Enhancing Technologies Workshop Proceedings
On April 25, 2025, the Future of Privacy Forum and the Mozilla Foundation co-hosted a Privacy Enhancing Technologies (PETs) Workshop in Washington, DC, convening industry, academia, and civil society experts to explore practical applications of PETs. The workshop featured two leading-edge use cases: Mastercard’s cross-border fraud detection system using Fully Homomorphic Encryption (FHE), and Oblivious’s […]
PETs Use Case: Differential Privacy for End-of-Life Data
In this use case, Oblivious partnered with an insurance company to tackle a common tension between data privacy and utility: how to retain meaningful insights from personal data while complying with legal requirements to delete it. By applying Differential Privacy, the organization can preserve actuarial insights without violating global privacy laws, generating differentially private statistical […]
Use Case: Preventing Financial Fraud Across Different Jurisdictions with Fully Homomorphic Encryption
Mastercard’s use of Fully Homomorphic Encryption (FHE) demonstrates how Privacy Enhancing Technologies (PETs) can support fraud detection across borders without compromising sensitive data. In this use case, Mastercard collaborated with Singapore’s Infocomm Media Development Authority to pilot a system that allows encrypted International Bank Account Numbers (IBANs) to be checked for fraud risk without revealing […]
Confidential Computing And Privacy: Policy Implications of Trusted Execution Environments
Confidential computing leverages two key technologies: trusted execution environments and attestation services. The technology allows organizations to restrict access to personal information, intellectual property, or sensitive or high-risk data through a secure hardware-based enclave or “trusted execution environment” (TEE). Economic sectors that have led the way in adopting confidential computing include financial services, healthcare, and […]
FPF Files Comments on White House Office of Science and Technology Policy Actions to Advance Privacy-Enhancing Technologies
FPF Files Comments on White House Office of Science and Technology Policy Actions to Advance Privacy-Enhancing Technologies On July 8, 2022, FPF filed comments with the White House Office of Science and Technology Policy (OSTP) regarding specific actions that would advance the adoption of privacy-enhancing technologies (PETs). As emerging technologies continue to offer increased speed, […]