FHE: The Ultimate Solution for Data Privacy Protection

FHE( Fully Homomorphic Encryption ) is an advanced encryption technology that allows computation to be performed directly on encrypted data, thereby processing data while protecting privacy. This technology has broad application prospects in various fields such as finance, healthcare, and cloud computing, but currently faces issues such as huge computational overhead and poor scalability, requiring further technological breakthroughs for commercialization.

The Basic Principles of FHE

The core of FHE is to hide the original information through polynomials and convert the computation into the form of a circuit. The entire process includes:

1. Choose the key polynomial, random polynomial, and small "error" polynomial.
2. Use these polynomials to encrypt the original text
3. Convert the computation into circuit form
4. Use key switching, modulus switching, and bootstrapping techniques to manage noise.

The most critical aspect is the guiding ( Bootstrap ) technology, which can reset noise to its initial level, enabling computations of infinite depth. Currently, mainstream FHE schemes such as TFHE, CKKS, etc., all utilize guiding technology.

Main Challenges Facing FHE

The biggest problem with FHE is the excessive computational overhead. Taking AES-128 decryption as an example, the computational time of the FHE version is about 500 million times that of the ordinary version. This is mainly due to the additional overhead brought by cryptographic indirect computation processes and techniques such as bootstrapping.

To address this issue, the U.S. DARPA launched the DPRIVE program, aiming to increase the speed of FHE computations to one-tenth that of normal computing. The program primarily focuses on the following aspects:

1. Increase the processor word length
2. Build dedicated ASIC processors
3. Adopting MIMD parallel architecture

Although the DPRIVE project is about to end, it has not yet reached the expected goals, and there is still a long way to go for the performance improvement of FHE.

The Application of FHE in Blockchain

In the blockchain field, FHE is mainly used to protect on-chain data privacy, including:

• On-chain privacy transactions
• AI Training Data Privacy Protection
• On-chain voting privacy
• MEV protection, etc.

However, due to performance limitations, the current application of FHE in blockchain is still limited.

Introduction to Major FHE Projects

The current FHE projects in the blockchain field mainly include:

• Zama: Provides a development toolchain based on TFHE
• Fhenix: Building a Privacy-First Optimism Layer 2
• Privasea: Data privacy protection for LLMs
• Inco Network: Building FHE Layer 1
• Arcium: A fusion of multiple cryptographic technologies
• Octra: A new type of FHE implementation based on hypergraphs

Future Prospects of FHE

FHE technology is still in its early stages, and there is still a long way to go before large-scale commercial applications can be realized. Future development mainly depends on the following aspects:

1. Development Progress of Dedicated FHE Chips
2. More efficient FHE algorithms
3. Continuous Investment of Capital
4. Implementation in key areas such as national defense, finance, and healthcare.

Despite facing numerous challenges, FHE, as a highly promising privacy protection technology, is still worth looking forward to in the future. With continuous technological breakthroughs and the expansion of application scenarios, FHE is expected to achieve explosive growth in the future, bringing revolutionary changes to data privacy protection.