Fully Homomorphic Encryption: A Revolutionary Breakthrough in Privacy Protection and Computation

Fully Homomorphic Encryption ( FHE ) is an advanced encryption technology that allows computations to be performed on encrypted data without first decrypting it. This concept was first proposed in the 1970s, but it was not realized until Craig Gentry's groundbreaking work in 2009. The core feature of FHE is homomorphism, which means that operations on ciphertext are equivalent to the corresponding operations on plaintext.

FHE supports unlimited addition and multiplication operations, making it a powerful privacy protection tool. However, FHE also faces challenges such as computational efficiency and noise management. Compared to some homomorphic encryption ( PHE ) and certain homomorphic encryption ( SHE ), FHE is more comprehensive in functionality but also has a larger computational overhead.

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 retaining the control capabilities of smart contracts. Some projects are developing FHE virtual machines that allow programmers to write code to operate FHE primitives using Solidity. This approach can enable applications such as encrypted payments and privacy-protecting games, while maintaining transaction graphs to meet regulatory requirements.

FHE can also improve the usability of privacy projects by enabling private message retrieval (OMR) to address issues such as long retrieval times for balance information and synchronization delays. Although FHE itself cannot directly solve blockchain scalability issues, combining it with zero-knowledge proofs (ZKP) may bring new solutions for scalability.

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 may increase computational complexity, but it can be necessary in certain use cases.

Currently, the development of FHE is approximately 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 the computational overhead of FHE is still higher than that of ZKP, its potential for large-scale applications is becoming evident.

The main challenges faced by FHE include computational efficiency and key management. The computational intensity of bootstrapping operations is being improved through algorithmic enhancements and engineering optimizations. For specific use cases like machine learning, there may be more efficient alternatives that do not use bootstrapping operations. In terms of key management, some projects adopt threshold key management methods, but further development is still needed to overcome single point of failure issues.

The FHE market is attracting more and more investments. Multiple projects are developing FHE-based solutions, such as Arcium, Cysic, Zama, Sunscreen, Octra, Fhenix, Mind Network, and Inco. These projects cover a wide range of application areas from hardware acceleration to privacy-preserving blockchain.

The regulatory environment's attitude towards privacy technologies such as FHE varies across different regions. While data privacy is widely supported, financial privacy remains a gray area. FHE has the potential to enhance data privacy, allowing users to retain data ownership and possibly profit from it, while still maintaining societal benefits like targeted advertising.

Looking to the future, the theory, software, hardware, and algorithms of FHE are expected to continue improving, making it increasingly practical. FHE is transitioning from theoretical research to practical application, and significant progress is anticipated in the next three to five years.

As technology matures and venture capital continues to pay attention, FHE is expected to play a key role in blockchain scalability and privacy protection, driving the development of various innovative applications in the encryption ecosystem.