Privacy-Enhancing Technologies

Secure Multi-Party Computation (MPC) enables collaborative computation without revealing individual inputs. Web applications could perform analytics, fraud detection, or personalization without accessing raw user data. Homomorphic encryption allows computation on encrypted data without decryption. These technologies promise functionality without privacy compromise, extending beyond HTTPS's transmission protection to computation protection.

Decentralized identity systems reduce reliance on centralized authentication providers. Blockchain-based identity, self-sovereign identity, and verifiable credentials enable users to control their identity information. Zero-knowledge proofs allow authentication without revealing underlying data. These systems could fundamentally change how identity works on the web, with HTTPS providing secure transport for decentralized protocols.

Privacy-preserving analytics and advertising technologies address the tension between business needs and user privacy. Differential privacy adds noise to data while preserving statistical properties. Federated learning enables model training without centralizing data. Privacy-preserving attribution provides advertising effectiveness measurement without tracking individuals. These technologies enable sustainable business models while respecting privacy.

Trusted Execution Environments (TEEs) provide hardware-based security for sensitive computations. Intel SGX, ARM TrustZone, and similar technologies create isolated execution environments. Web applications could leverage TEEs for client-side security, protecting against malware and ensuring computation integrity. Remote attestation enables servers to verify client security posture. These hardware features complement HTTPS with execution protection.