Veracruz is introduced as a comprehensive framework designed for privacy-preserving collaborative computations involving multiple data owners with a centralized program owner. The framework's strengths lie in its adaptability, allowing for various computations defined by global policies that dictate data flow among participants. By adjusting the number of participants and the specifics of the program, Veracruz can effectively model diverse interaction patterns essential for secure data collaboration. This flexibility is crucial for applications requiring stringent privacy protections while still supporting collaborative analysis of sensitive information.
Veracruz provides a flexible framework for secure collaborative computations, accommodating various data owners while ensuring privacy-preserving operations through adaptable programmatic and policy variations.
The framework's unique approach allows it to integrate multiple data owners, facilitating collaborative work without compromising on security or privacy—essential for sensitive data usage.
Collection
[
|
...
]