Secure Computation
Secure computation is a cryptographic technique that enables multiple parties to jointly compute a function over their private inputs without revealing those inputs to each other. It ensures data privacy and confidentiality while allowing collaborative analysis, such as in privacy-preserving machine learning or secure voting systems. This concept includes protocols like secure multi-party computation (MPC), homomorphic encryption, and zero-knowledge proofs.
Developers should learn secure computation when building applications that require privacy-sensitive data processing, such as in healthcare, finance, or government sectors, where sharing raw data is prohibited or risky. It is essential for implementing privacy-by-design systems, enabling secure data analytics across organizations without compromising individual privacy, and is increasingly relevant with regulations like GDPR and HIPAA.