The Development and Application Prospects of Fully Homomorphic Encryption

Fully Homomorphic Encryption (FHE), as an advanced encryption technology, has been a focus of attention since it was first proposed in the 1970s. In 2009, Craig Gentry's groundbreaking research paved the way for the practical application of FHE. FHE allows computation on encrypted data without the need for decryption, a feature that holds great potential for protecting data privacy.

The core features of FHE include homomorphic property, noise management, and support for unlimited operations. Compared to partially homomorphic encryption and some forms of homomorphic encryption, FHE can support unlimited addition and multiplication operations, allowing it to perform any type of computation on encrypted data.

In the blockchain field, FHE is expected to become a key technology for solving scalability and privacy protection issues. It can transform a transparent blockchain into a partially encrypted form while maintaining control over smart contracts. Some projects are developing virtual machines based on FHE, allowing programmers to write smart contract code that operates FHE primitives. This approach not only addresses current privacy issues on the blockchain but may also enable applications such as encrypted payments and online gambling.

FHE can also improve the usability of privacy projects through Oblivious Message Retrieval (OMR), addressing long-standing issues such as balance information retrieval and synchronization delays. Although FHE itself cannot directly solve the scalability issues of blockchain, combining it with Zero-Knowledge Proofs (ZKP) may provide solutions to this challenge.

FHE and ZKP are complementary technologies, each serving different purposes. ZKP provides verifiable computation and zero-knowledge properties, while FHE allows computation on encrypted data without exposing the data itself. Combining the two, while increasing computational complexity, may provide significant advantages in specific scenarios.

Currently, the development of FHE is about three to four years behind ZKP, but it is catching up rapidly. The first generation of FHE projects has begun testing, and the mainnet is expected to be launched later this year. Although FHE still faces challenges such as computational efficiency and key management, its potential for mass adoption is gradually becoming evident.

In the market, several companies are actively developing technologies and applications related to FHE. For example, Zama focuses on developing FHE solutions for blockchain and AI; Sunscreen provides an FHE compiler to help engineers build private applications; Fhenix is developing an Ethereum Layer 2 network based on FHE; Mind Network is dedicated to applying FHE in the fields of DePIN and AI.

In terms of regulatory environment, FHE as a privacy technology has varying regulatory attitudes across different regions. Although data privacy is generally supported, financial privacy remains a field that requires careful handling. FHE has the potential to protect personal data ownership while also bringing societal benefits such as targeted advertising.

With the continuous advancement of theoretical research, software development, hardware optimization, and algorithm improvement, FHE is gradually transitioning from the theoretical stage to practical applications. It is expected that in the next three to five years, FHE will achieve significant progress in the field of encryption, bringing revolutionary changes to blockchain scalability and privacy protection, and promoting the development of various innovative applications in the encryption ecosystem.