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Privacy Enhancing Technology Sandboxes

Experiment with digital solutions that safely extract value from data.

What are Privacy Enhancing Technologies?

Privacy Enhancing Technologies (PETs) enable businesses to obtain valuable insights from data while ensuring personal data protection, data privacy, and the safeguard of commercially sensitive information. PETs allow for increased B2B data collaboration, cross-border data flow, and data collection for AI development.

IMDA’s PET Sandbox: A safe space to trial PETs

As PETs are still in their infancy, there is much to learn about using these technologies in a real-world environment. To facilitate experimentation with PETs, IMDA’s PET Sandbox – Singapore’s first – provides opportunities for companies to work with trusted PET digital solution providers to develop use cases and pilot PETs.

The PET Sandbox will:

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Matchmake use case owners to a panel of PET digital solution providers.

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Provide grant support to user companies to scope and implement pilot projects.

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Provide regulatory support to ensure that PETs are deployed in a compliant manner.

Unlock value from data with IMDA's Privacy Enhancing Technology Sandbox

Unlock value from data with IMDA's Privacy Enhancing Technology Sandbox

Case studies

Since the launch of the PET Sandbox, IMDA has received active participation from the industry. Read about the PET use cases implemented by the participating businesses: 

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GPAI | Overcoming data barriers via Trustworthy Privacy Enhancing Technologies

GPAI and IMDA collaborated to demonstrate how privacy-enhancing technologies can be used to share data from past pandemics and improve societal resilience to future outbreaks. This report shares key findings from this project, highlighting the importance of circulating data via confidential and trustworthy channels.

Learn how trustworthy privacy-enhancing technologies can be used to overcome data barriers (1.41MB).

Healthcare Services Provider | Accessing more data through Trusted Execution Environment to generate new insights

Data sharing amongst the pharmaceutical company and its data partners has not been easy as they have to abide to the different data protection regulations in various jurisdictions. Often these data involves individuals and may disclose product distribution and transaction data within the ecosystem players. The pharmaceutical company designed a Trusted Execution Environment (TEE) based solution for the POC, where it included safeguards to ensure that the original data from data partners cannot be read, modified, or accessed in any form by host of the environment. Through the POC, the company managed to access more data from its data partners and create new data models that benefits the ecosystem partners. 

Find out how more data can be accessed through Trusted Execution Environment to generate new insights (280.69KB).

Mastercard | Preventing financial fraud across different jurisdictions with secure data collaborations

Mastercard, a global technology company in the payments industry, via its Cyber and Intelligence Solutions business line has been assessing the potential for frontier technologies, including Privacy Enhancing Technologies (PETs), to buttress its product offerings against financial crimes like money laundering.

Mastercard developed a proof of concept (POC) in IMDA’s PET Sandbox program to investigate a product based on Fully Homomorphic Encryption (FHE), provided by a third-party supplier, for sharing financial crime intelligence across international borders – specifically between Singapore, the United States (“US”), India and the United Kingdom (“UK”) – while complying with prevailing regulations.

Learn how an AML solution built with Fully Homomorphic Encryption can comply with financial regulations (365.61KB).

Meta | Digital advertising in a paradigm without 3rd party cookies

Tracking technologies, like 3rd party cookies, are presently a mainstay in the digital advertising ecosystem. Publishers, advertisers and adtech firms rely on the collection and sharing of user / device identifiers to analyse how consumers can be shown advertisements best aligned to their online interests or activities.

However, the ecosystem is preparing for a paradigm in which the collection of user / device identifiers that are linkable across apps / websites is no longer feasible, and trust in the ecosystem is low. A prominent avenue where solutions to measure attribution of digital ads without tracking technologies is actively discussed is the World Wide Web Consortium (W3C)’s Private Advertising Technology Community Group, or “PAT-CG”.

Meta and Mozilla, as members of PAT-CG, have proposed a solution – “Interoperable Private Attribution” or IPA. It uses a combination of multiparty computing (MPC), aggregation, differential privacy (DP) and write-only identifiers to enable attribution measurement. The solution aims to measure advertising outcomes based on impressions shown on publisher website(s)/app(s) and conversions occurring on an advertiser website/app.

Find out how Meta and its partners piloted ‘Interoperable Private Attribution’ (439.36KB), a PET-based solution to generate attribution reports without use of 3rd party cookies.

Companies with PET use cases are invited to participate in the PET Sandbox. More information can be found in the invitation to participate in the PET Sandbox (202.63KB).

For insights into PETs and the PET Sandbox, please access the following reports.

IMDA-Google: PET x Privacy Sandbox

IMDA has partnered with Google to give companies access to Google’s Privacy Sandbox through IMDA’s PET Sandbox environment. Key features of the PET x Privacy Sandbox include:

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Open to all Singapore-registered companies interested in learning about, and testing, PETs. Be a part of the privacy-first shift across web and mobile applications.

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Companies will learn about protecting user privacy and be equipped with tools to do so while extracting data value.

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Publishers and developers will learn privacy-preserving alternatives to access data on sites and apps for business needs.

Find out more about the PET x Privacy Sandbox here.

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