One key method for ensuring privacy while processing large amounts of data is de-identification. De-identified data refers to data through which a link to a particular individual cannot be established. This often involves “scrubbing” the identifiable elements of personal data, making it “safe” in privacy terms while attempting to retain its commercial and scientific value.
In the era of big data, the debate over the definition of personal information, de-identification and re-identification has never been more important. Privacy regimes often rely on data being considered Personal in order to require the application of privacy rights and protections. Data that is anonymous is considered free of privacy risk and available for public use.
Yet much data that is collected and used exists somewhere on a spectrum between these stages. FPF’s De-ID Project has examined practical frameworks for applying privacy restrictions to data based on the nature of data that is collected, the risks of de-identification, and the additional legal and administrative protections that may be applied.
No Silver Bullet, But a Silver Lining? PETs and International Data Transfers
Is there a role for Privacy Enhancing Technologies (PETs) to play in the context of international data transfers? The answer to this question could be one of the keys to unlock trusted cross-border data flows at scale in the age of AI. This was the topic explored in a session organized by the Future of […]
NEW FPF REPORT: Confidential Computing and Privacy: Policy Implications of Trusted Execution Environments
Written by Judy Wang, FPF Communications Intern Today, the Future of Privacy Forum (FPF) published a paper on confidential computing, a privacy-enhancing technology (PET) that marks a significant shift in the trustworthiness and verifiability of data processing for the use cases it supports, including training and use of AI models. Confidential computing leverages two key […]
Event Report: FPF Side Event and Workshop on Privacy Enhancing Technologies (PETs) at the 2022 Global Privacy Assembly (GPA)
The 2022 Global Privacy Assembly (GPA) – which brings together most global data protection authorities (DPAs) every year since 1979, to share knowledge and establish common priorities among regulators – took place between October 25 and 28, in Istanbul (Türkiye). The Future of Privacy Forum (FPF) was invited by the organizers of the GPA (the […]