PETSpaces (Privacy-Enhancing Data App for Secure Computations in Data Spaces)
This data app focuses on enabling privacy-preserving computations in data spaces. It leverages advanced Privacy-Enhancing Technologies (PETs), currently featuring Fully Homomorphic Encryption (FHE) and planned support for approaches like anonymization techniques and Zero-Knowledge Proofs (ZKPs). It
Purpose
This tool provides secure and private computation capabilities, directly supporting DSSC’s objectives of safer data sharing and data sovereignty.
About
This data app focuses on enabling privacy-preserving computations in data spaces. It leverages advanced Privacy-Enhancing Technologies (PETs), currently featuring Fully Homomorphic Encryption (FHE) and planned support for approaches like anonymization techniques and Zero-Knowledge Proofs (ZKPs). It is offered in the data space and delivered as a ready-to-deploy app to be instantiated in EDC connectors. It allows participants to process and compute encrypted data, preserving data privacy and enhancing data owners’ sovereignty over their data.
Building blocks
Supported standards
Blueprint compliance
Details
- Technology readiness level
- TRL 3
- Domain / sector / industry
- Cross-Domain Solution: Energy, Industrial Manufacturing, Industry 4.0, Healthcare.
- Geographical application area
- Global, with a primary focus on Europe due to alignment with European data sovereignty standards (e.g., GDPR) and initiatives (European Health Data Space (EHDS)).
- Deployments in operation
- (Currently not applicable due to TRL below 7).
- Dependencies
- Eclipse Data Space Connector (EDC) under the Minimum Viable Data Space (MVD). Microsoft SEAL library for HE computation. Docker infrastructure for component deployment.
- Business offerings
- (Currently not applicable; under development and research phase).
- Additional functionalities
- PETSpaces data app integrates Eclipse Data Space Connector (EDC) with Microsoft SEAL for HE-enabled data computations, ensuring data privacy and data owner’s sovereignty.
- Similar/competing implementations
- Not acknowledged similar tools.
Works well with
Complementary solutions.
Data Models
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Data Models
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Compatible protocols, complementary blocks
Data Models
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Community rating
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