FHE: The Future of Privacy Computing

FHE( Fully Homomorphic Encryption) is an advanced encryption technology that allows computation on encrypted data, thereby processing data while protecting privacy. FHE has broad application prospects in data processing fields that require privacy protection, such as finance, healthcare, and cloud computing. However, due to its large computational overhead, commercialization still requires time.

Basic Principles

The core of FHE is to hide the plaintext information through polynomials and convert the computation into a circuit model. To solve the problem of noise accumulation, FHE employs techniques such as key switching, modulus switching, and bootstrapping. Currently, mainstream FHE schemes include BGV, BFV, CKKS, etc., all of which use bootstrapping technology to achieve computation of unlimited depth.

Challenges Faced

The biggest challenge of FHE lies in its enormous computational overhead, which can be up to 500 million times slower than ordinary computation. To address this, DARPA launched the DPRIVE program, aimed at improving the computation speed of FHE to 1/10th of ordinary computation. The program focuses on increasing processor word length, designing dedicated ASICs, and building MIMD parallel architectures, but progress has been slow and the expected goals have not yet been achieved.

Blockchain Integration

In the blockchain field, FHE can be used to protect on-chain privacy, AI training data privacy, on-chain voting privacy, and more. Some projects attempt to apply FHE to solve the MEV problem, but they also face challenges such as inefficiency and the disappearance of positive externalities.

Main Projects

The main projects in the FHE field currently include:

• Zama: Based on the TFHE scheme, a relatively complete FHE development stack has been built.
• Octra: Implements FHE using hypergraph technology, creating a new smart contract language.
• Fhenix: A privacy-first Layer 2 built on Zama technology
• Privasea: Using FHE for LLM data operations
• Inco Network: Built on fhEVM Layer 1
• Mind Network: Combining FHE with Restaking

Development Prospects

FHE technology is still in its early stages, facing challenges such as low efficiency and high engineering difficulty. However, with more capital attention and the development of dedicated chips, FHE is expected to bring about transformation in privacy-sensitive fields such as national defense, finance, and healthcare. The implementation of FHE chips will be key to its commercialization. Despite the numerous challenges, FHE, as an advanced technology with clear demand, holds promise for future development.