MaskingMasking: Privacy’s First Shield.
We develop efficient masking techniques that enhance data privacy in AI computations. Our approach leverages Substrate to enable secure, privacy-preserving processing.
Advanced Masking Techniques for Data Privacy
We aim to develop efficient, application-specific masking techniques that integrate with Homomorphic and differential privacy to provide robust privacy guarantees while minimizing computational overhead, enhancing the ZKP Ecosystem’s ability to protect sensitive data during AI computations within Substrate’s runtime environment.
Our masking research leverages Substrate’s modular pallet architecture and off-chain workers to enable privacy-preserving computations that integrate seamlessly with the ZKP Blockchain’s BABE+GRANDPA consensus mechanism and native verification infrastructure.
In this section we will showcase future research initiatives of Masking.
Keep Exploring Masking
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Homomorphic Masking
Hybrid Privacy Models
Selective Masking
Performance Optimization
Integration With Zkp
Example Application
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