Fully Homomorphic Encryption: A New Chapter in Privacy Computing

The concept of Fully Homomorphic Encryption (FHE) originated in the 1970s, but it wasn't until 2009 that it made groundbreaking progress. Craig Gentry demonstrated the possibility of performing arbitrary computations on encrypted data, thereby advancing the development of FHE.

FHE is an advanced encryption technology that allows computations on encrypted data without decryption. This means that operations can be performed on ciphertext and generate encrypted results, with the decrypted result being consistent with the result of performing the same operations on the plaintext.

Key Features of FHE

1. Homomorphic property: The addition and multiplication operations of ciphertext correspond to the respective operations of plaintext.

2. Noise Management: During the FHE encryption process, noise is added to ensure security, but as the number of operations increases, the noise will also accumulate. Effectively managing noise is crucial for maintaining computational accuracy.

3. Unlimited Operations: Compared to other homomorphic encryption schemes, FHE supports unlimited additions and multiplications.

The main advantage of FHE is that it can perform arbitrarily complex computations while protecting data privacy.

The Application of FHE in Blockchain

FHE is expected to become a key technology for blockchain scalability and privacy protection. It can transform a transparent blockchain into a partially encrypted form while maintaining control of smart contracts. This technology can enable applications such as encrypted payments and privacy games, while retaining transaction graphs to meet regulatory requirements.

FHE can also improve the user experience of privacy projects through Oblivious Message Retrieval (OMR), allowing wallet clients to sync data without exposing the accessed content.

The Relationship Between FHE and Zero-Knowledge Proofs

FHE and Zero-Knowledge Proofs (ZKP) are complementary technologies. ZKP provides verifiable computation and zero-knowledge properties, while FHE allows computations on encrypted data without exposing the data. Combining the two may significantly increase computational complexity, so it is only considered when specific use cases require it.

Current Status and Future Prospects of FHE

The development speed of FHE is accelerating, and it is expected to achieve large-scale application in the coming years. The first generation of FHE projects has begun testing, with the mainnet expected to launch later this year. Although the computational overhead of FHE is still higher than that of ZKP, its application potential is enormous.

Challenges and Bottlenecks

The main challenges facing FHE include computational efficiency and key management. Bootstrapping operations are computation-intensive, but algorithm optimization is continuously improving. Key management also needs further development to overcome single point of failure issues.

Current Status of the FHE Market

Encryption venture capital firms are actively investing in the FHE field. Threshold FHE (TFHE) combines FHE, multiparty computation, and blockchain technology, opening up new application scenarios. The developer-friendliness of FHE makes it both practical and feasible in application development.

Regulatory Environment

FHE faces different regulatory environments in different regions. While data privacy is generally supported, financial privacy remains a complex area. FHE has the potential to enhance data privacy protection while maintaining social benefits.

Conclusion

Fully homomorphic encryption is at a critical moment in transforming the encryption field. With continuous technological advancements and sustained capital attention, FHE is expected to achieve widespread application in the coming years, providing innovative solutions for blockchain scalability and privacy protection, and promoting further development of the encryption ecosystem.