Privacy-Preserving Analytics

Definition ∞ Privacy-preserving analytics refers to methods and technologies that allow for the analysis of data, often on a blockchain, while maintaining the confidentiality of individual data points or user identities. Techniques like zero-knowledge proofs, homomorphic encryption, and differential privacy are employed to extract insights without exposing sensitive information. This balances data utility with privacy.
Context ∞ News frequently discusses privacy-preserving analytics in relation to regulatory compliance, data security concerns in decentralized finance (DeFi), and the ethical use of blockchain data. Its development is critical for enabling institutional adoption and for applications requiring both transparency and confidentiality. Advancements in this field aim to unlock new use cases for sensitive data on public ledgers.