Privacy Preserving Computation
What is Privacy Preserving Computation?
Technologies that enable data analysis and processing while protecting the privacy of underlying personal data, including homomorphic encryption.
Frameworks that govern privacy preserving computation
What the standards actually require on privacy preserving computation
Requirements naming privacy preserving computation across this standard, quoted from the control text.
Categorises Privacy-Enhancing Technologies (PETs) and frames how each addresses data protection principles. Three broad categories underpin the report: anonymisation/pseudonymisation, privacy-preserving computation, and PETs for access/communication/storage;
ENISA-DPE-2.3 · Privacy-Enhancing Technologies (overview and taxonomy) →Questions people ask about privacy preserving computation
What is Privacy Preserving Computation?
Technologies that enable data analysis and processing while protecting the privacy of underlying personal data, including homomorphic encryption.
Why is Privacy Preserving Computation important for compliance?
Privacy Preserving Computation is a key concept in Privacy and Data Protection. Understanding privacy preserving computation helps organizations meet regulatory requirements, reduce risk, and demonstrate due diligence during audits. Our compliance platform maps 686 frameworks with 311K cross-framework control mappings.
Which compliance frameworks address Privacy Preserving Computation?
Privacy Preserving Computation appears in the requirement text of ENISA Data Protection Engineering - From Theory to Practice. Across these standards we have identified 1 control that names it directly, each linked to the control text on the compliance platform.
Where can I learn more about Privacy Preserving Computation?
Explore our compliance framework pages to see how privacy preserving computation applies across different standards and regulations. Our implementation guides provide step-by-step guidance, and the compliance platform offers AI-powered analysis of how this concept maps across 686 frameworks.
See how Privacy Preserving Computation applies across compliance frameworks
Our platform maps 686 frameworks with 311K cross-framework control mappings. Explore how this concept is addressed across standards.
Written and maintained by Gerard Blokdyk, The Art of Service.