Privacy Preserving Computation
Privacy Preserving Computation (PPC) is a set of cryptographic techniques and protocols that enable data analysis and computation on sensitive information without exposing the raw data. It allows multiple parties to collaboratively compute functions over their private inputs while keeping those inputs confidential. This includes methods like secure multi-party computation, homomorphic encryption, and differential privacy.
Developers should learn PPC when building applications that handle sensitive data in regulated industries like healthcare, finance, or government, where data privacy is legally mandated. It's essential for implementing federated learning systems, privacy-preserving analytics, and secure data sharing platforms where trust between parties is limited. PPC enables compliance with regulations like GDPR and HIPAA while still extracting value from confidential datasets.