Beyond ZKP? A quick look at 5 potential projects for fully homomorphic encryption

Author: Degen Maker;Compiled by: Luffy, Foresight News

Quantong State-of-the-art encryption (FHE) is quickly becoming a buzzword, and do you know why?

FHE allows calculations on encrypted data without leaking any information, opening up a variety of possibilities for Web3, including but not limited to:

• Confidentiality RWA tokenization

• On-chain identity

• MEV protection

• On-chain medical data with privacy

• Making DeFi compliant with data protection and privacy laws

In addition, FHE can also be used in Web3 The field combined with artificial intelligence and zero-knowledge proof comes into play.

AI models can now leverage data and generate results without accessing the actual input data, ensuring that user queries remain private and secure. This also means that data training can be performed without direct access to the data.

While debate continues over the closed-source nature of the major big language modeling companies, FHE has emerged as a potential game-changer in artificial intelligence.

Many people are debating whether FHE will replace zero-knowledge proofs (ZKP); however, they can coexist. ZKP can be used to generate private proofs, while FHE can handle data processing in smart contracts.

FHE is still in the early stages of development. I will briefly introduce 5 FHE projects with potential.

1) Inco

Inco is a modular confidentiality-as-a-service as-a-service) blockchain, which is EVM-compatible L1 and fully powered by FHE.

Inco previously completed a $4.5 million seed round led by 1kx.

Catalysts and takeaways:

• Providing privacy at the base layer is a strong value proposition that can attract many privacy-focused DApps.

• The introduction of the data availability layer has revolutionized the ecosystem of modular projects like Celestia. Layers of secrecy are expected to have similar, if not greater, appeal.

• Partnering with Zama, for which the Polygon co-founder is an advisor, will borrow Ethereum’s security through EigenLayer (actually AVS) sex.

2) Mind Network

Mind is a security and a data privacy Zero Trust Layer designed to facilitate true CrossFi scaling.

Mind has completed a $2.5 million seed round led by Binance Labs.

Catalysts and takeaways:

• Building Internet infrastructure that empowers citizens around the world to control their data.

• The testnet has been launched, and incentives may be provided for the testnet.

• Powered by Zama.

• The first use case is MindLake, a groundbreaking data storage Rollup designed to improve the Encrypt data for calculations.

3) Fhenix

Fhenix is ​​the first The Rollup-based FHE architecture is designed to address the challenges of performing FHE computations on L1 due to extensive execution requirements and scalability limitations.

Catalysts and takeaways:

• Optimistic FHE Rollup can be built on Ethereum without modifying the base layer, which means every smart contract in Ethereum can have enhanced privacy through the FHE Rollup solution.

• Working with Zama to launch fhEVM infrastructure.

• The testnet will be launched soon.

• In my opinion, Fhenix simplifies the deployment of confidential smart contracts, which is critical for developer adoption.

4) Privasea

Privasea is a tool that uses FHE To ensure privacy and security in the AI ​​computing process.

Privasea has completed a $5 million seed round led by Binance Labs.

Catalysts and takeaways:

• Genesis NFT details will be announced soon, and holders will be able to receive airdrops.

• Provide private computing FHE solutions for DePIN+AI, combine all hot spots into a legitimate and promising project, and project tokens Potentially high returns.

• Another DApp is being developed for secure and private user verification, ensuring privacy in the KYC process without exposing personal details , but remain auditable when necessary.

• Powered by Zama.

5) Optalysys

Optalysys is building the next generation In terms of computing processing power, I think this is a very promising project and a "shovel" in the FHE field.

Optalysys focuses on the DePIN project, which has a cloud-native technology stack tailored for high-intensity FHE workloads, facilitating FHE in the compute layer Extension.

Catalysts and takeaways:

• Potential as a shovel.

• Coprocessors (GPU, CPU) address fundamental limitations of electronic systems.

• Optalysys develops a unique optical computing system that delivers processing power and energy efficiency from the data center to edge computing, All major FHE libraries are supported.