The Development and Application of Fully Homomorphic Encryption Technology

Fully Homomorphic Encryption (FHE) is an advanced encryption technology that allows computations to be performed on encrypted data without decrypting it. This concept was first proposed in the 1970s, but it wasn't until 2009 that significant breakthroughs were made. Craig Gentry demonstrated a method to perform arbitrary computations on encrypted data, marking the birth of FHE.

The core features of FHE include homomorphism, noise management, and unlimited operations. Homomorphism means that operations on ciphertext are equivalent to operations on plaintext, including addition and multiplication. Noise management is crucial for ensuring the accuracy of computations, as each operation increases noise. Unlike partial homomorphic encryption and some homomorphic encryption, FHE supports unlimited addition and multiplication operations.

In the blockchain field, FHE is considered a potential technology for addressing 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 FHE virtual machines that allow programmers to write smart contract code that operates FHE primitives. This approach holds promise for solving current privacy issues on the blockchain, enabling applications such as encrypted payments and gaming, while retaining transaction graphs to meet regulatory requirements.

FHE can also improve the usability of privacy projects, such as solving wallet synchronization issues through Oblivious Message Retrieval (OMR). However, FHE itself does not directly address the scalability issues of blockchain and may need to be combined with Zero-Knowledge Proofs (ZKP) to tackle this challenge.

FHE and ZKP are complementary technologies, each with its advantages. ZKP provides verifiable computation and zero-knowledge properties, while FHE allows computation without exposing data. Combining the two may significantly increase computational complexity, so a trade-off needs to be made based on specific use cases.

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 launch later this year. Although the computational overhead of FHE is still higher than that of ZKP, its potential for large-scale application is becoming evident.

The main challenges facing FHE include computational efficiency and key management. The computational intensity of bootstrapping operations is being alleviated through algorithmic improvements and engineering optimizations. In terms of key management, some projects are exploring threshold key management schemes, but further development is still needed to overcome single point of failure issues.

In the market, several companies are actively developing technologies and applications related to FHE. These companies include Arcium, which focuses on confidential computing; Cysic, which provides ZK computing as a service; Zama, which develops FHE solutions; Sunscreen, which builds private applications; Octra, which launches FHE blockchain networks; Fhenix, which develops Ethereum Layer 2 supported by FHE; Mind Network, which builds an FHE re-staking layer; and Inco Network, which offers modular confidential computing solutions.

In terms of regulatory environment, FHE has the potential to enhance data privacy while maintaining social benefits. With continuous advancements in theory, software, hardware, and algorithms, FHE is expected to achieve significant development in the next three to five years, gradually transitioning from theoretical research to practical applications.

Overall, FHE, as a revolutionary technology, is bringing transformation to the field of encryption, promising to address key issues of blockchain scalability and privacy protection, and opening new possibilities for various innovative applications.