Fully Homomorphic Encryption: The New Frontier of Blockchain Privacy and Scalability

Fully homomorphic encryption (FHE) is a groundbreaking encryption technology that allows computations to be performed on encrypted data without the need for decryption first. This concept can be traced back to the 1970s, but it wasn't until Craig Gentry's research in 2009 that significant breakthroughs were made, enabling the possibility of performing arbitrary computations on encrypted data.

The core features of FHE include homomorphic properties, noise management, and unlimited operational capabilities. It supports addition and multiplication operations on ciphertext, with results equivalent to performing the same operations on plaintext. However, FHE faces challenges in noise management and computational efficiency, as computations on ciphertext can be thousands to millions of times more expensive than those on plaintext.

In the field of Blockchain, FHE is expected to become a key technology for solving privacy and scalability 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, allowing programmers to write code using Solidity to operate FHE primitives, which may provide privacy protection solutions for applications such as encrypted payments and gaming.

FHE can also improve the user experience of existing privacy projects through Oblivious Message Retrieval (OMR), allowing wallet clients to synchronize data without exposing the content accessed. Although FHE itself does not directly address the scalability issues of Blockchain, it may provide solutions to certain scalability challenges when combined with Zero-Knowledge Proofs (ZKP).

FHE and ZKP are complementary technologies that address different privacy needs. ZKP provides verifiable computation and zero-knowledge properties, while FHE allows computation on encrypted data without exposing the data itself. Combining the two may significantly increase computational complexity, so a cost-benefit analysis should be conducted 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 go live later this year. Although FHE still faces challenges such as computational efficiency and key management, its potential for large-scale adoption is gradually becoming apparent.

In the market, multiple projects are driving the development and application of FHE. Arcium is developing a DePIN network on Solana for parallel confidential computing. Cysic focuses on hardware acceleration for real-time generation and verification of zero-knowledge proofs. Zama provides open-source FHE solutions for blockchain and AI applications. Sunscreen is developing an FHE compiler to help engineers build private applications. Octra has proposed a new type of FHE called HFHE that runs on hypergraphs. Fhenix is developing an Ethereum Layer 2 solution supported by FHE. Mind Network is dedicated to achieving an "end-to-end encrypted internet". Inco Network is building a modular confidential computing Layer 1 blockchain and a universal privacy layer for Web3.

With the continuous advancement of FHE technology, significant progress is expected in the next three to five years. It is anticipated to drive innovation in various applications within the encryption ecosystem, providing more robust privacy protection and scalability solutions for Blockchain. Despite facing complex regulatory environments in different regions, FHE has the potential to bring new possibilities for data ownership and utilization while protecting user privacy.