FHE: The Future Path of Privacy Computing

FHE (Fully Homomorphic Encryption) is an advanced encryption technology that allows computations to be performed directly on encrypted data, enabling data processing while protecting privacy. This technology has broad application prospects in privacy-sensitive fields such as finance, healthcare, and cloud computing. However, the commercialization of FHE still faces many challenges, primarily due to its large computational and memory overhead, as well as insufficient scalability.

Basic Principles of FHE

The core idea of FHE is to hide the original data through complex polynomial operations. Specifically:

1. Choose a key polynomial s(x)
2. Generate a random polynomial a(x)
3. Generate a small "noise" polynomial e(x)
4. Encrypted plaintext m: c(x) = m + a(x)*s(x) + e(x)

During decryption, as long as the key s(x) is known, m can be recovered from c(x). Introducing random polynomials and noise is to enhance security and prevent patterns from being inferred through simple repeated inputs.

However, the introduction of noise also brings challenges - as the number of computations increases, the noise can accumulate continuously, eventually making it impossible to decrypt correctly. To address this issue, FHE employs several techniques:

• Key switching: compress ciphertext size
• Modulus switching: controlling noise growth
• Bootstrap: Reset the noise to the initial level

Among them, Bootstrap is the key to achieving true FHE, but it is also the operation that consumes the most computational resources.

Challenges Faced by FHE

The biggest problem with FHE is the low computational efficiency. Even simple operations can incur costs that are billions of times higher than regular computations under FHE. To improve this situation, the U.S. Department of Defense Advanced Research Projects Agency ( DARPA ) launched the DPRIVE program in 2021, aiming to increase the computational speed of FHE to 1/10 of regular computations. The program mainly focuses on the following aspects:

1. Increase the processor word length to support larger moduli.
2. Develop dedicated ASIC processors
3. Build MIMD Parallel Architecture

Although the DPRIVE project is nearing completion, its progress seems to be less than expected. This indicates that the commercialization of FHE technology still requires time.

The Application of FHE in Blockchain

In the blockchain field, FHE is mainly used to protect data privacy, and application scenarios include:

• On-chain privacy protection
• AI Training Data Privacy
• On-chain voting privacy
• On-chain privacy transaction review
• Potential MEV solutions

However, the high computational overhead of FHE also poses challenges for its application in blockchain, potentially significantly reducing network throughput.

Main FHE Projects

The main projects in the field of FHE currently include:

• Zama: Provides a complete FHE development stack based on the TFHE scheme
• Fhenix: Building a Privacy-First Optimism Layer 2
• Privasea: Committed to the application of FHE in LLM data operations
• Inco Network: Building a Layer 1 network based on FHE
• Arcium: Integrating various cryptographic technologies such as FHE, MPC, and ZK.
• Mind Network: Exploring the application of FHE in the field of Restaking
• Octra: Implements FHE using unique hypergraphs technology

Future Outlook

Although FHE technology is still in its early stages and faces numerous challenges, its potential for privacy protection cannot be ignored. With more capital and talent being invested, as well as the development of dedicated hardware, FHE is expected to bring significant breakthroughs in the future. Especially in fields such as defense, finance, and healthcare, where data privacy requirements are extremely high, FHE could lead to profound changes.

The implementation of FHE chips will be a key milestone in the commercialization of this technology. Currently, several companies, including Intel, Chain Reaction, and Optalysys, are exploring this field. Once FHE chips mature and are combined with cutting-edge technologies such as quantum computing, they are expected to unleash tremendous innovative potential.