Privacy computing, also known as privacy-preserving computing, refers to a set of technologies and methodologies that enable data processing and analysis while protecting the privacy of individuals. This is particularly important in today's data-driven world where personal information is often collected and used by various entities.
Key Technologies
- Homomorphic Encryption (同态加密): Allows computations to be performed on encrypted data without decrypting it first.
- Secure Multi-Party Computation (安全多方计算): Enables multiple parties to compute a function over their inputs while keeping those inputs private.
- Differential Privacy (差分隐私): Adds noise to the data to protect the privacy of individuals while still allowing useful analysis.
Applications
Privacy computing has a wide range of applications, including:
- Healthcare: Protecting patient data while enabling research and analysis.
- Finance: Ensuring the privacy of financial transactions and customer data.
- Government: Safeguarding sensitive information while providing public services.
Learn More
For more information on privacy computing, you can visit our Privacy Computing Guide.
Privacy Computing