Apply masking [[ZKP/Research/Noise/Privacy Budget Management|only to sensitive features]] (e.g., patient identifiers in healthcare datasets), reducing overhead while maintaining privacy for critical data [102]. This aligns with the [[ZKP/Introduction/About|ecosystem's]] efficiency goals and [[Substrate]]'s optimized execution environment. Selective masking ensures that only the most sensitive elements of a [[ZKP/Data Marketplace/Tokenized Datasets/Comprehensive Mechanisms of Tokenized Datasets|dataset]] are obscured, leaving non-sensitive data untouched to minimize computational impact, which is crucial for real-time applications where speed is essential, such as in diagnostic AI systems processing live patient data through Substrate's high-performance runtime. See also: [[ZKP/Research/Masking/Performance Optimization|Performance Optimization]]