In the context of the integration of Web3 and AI, privacy computing has become the core infrastructure of the digital age. Decentralized Confidential Computing (DeCC) ensures data privacy and computational correctness through cryptographic technologies without relying on centralized hardware (such as TEE). Fully Homomorphic Encryption (FHE), as the core technology of DeCC, can achieve arbitrary universal computation in an encrypted state and is considered the ultimate solution for privacy computing.

1. What is DeCC?

Traditional confidential computing relies on TEE (such as Intel SGX), but there are risks of centralization and difficulties in integrating with Web3. DeCC achieves trustless privacy computing through cryptographic means (such as MPC, ZKP, FHE). FHE is the only technology that supports universal computation in an encrypted state, becoming a key pillar of DeCC.

2. Core Value of FHE

Black-box Computing Environment

FHE allows computing nodes to process data without decryption, preventing data leakage and addressing issues such as centralized server snooping, plaintext operation on-chain, and trust in multi-party cooperation.

Verifiable Results

FHE combined with ZKP ensures that the results of encrypted computations are valid and have not been tampered with, suitable for scenarios such as financial settlement, collaborative training, and DID verification.

3. FHE + HTTPZ: Zero Trust Computing Internet

HTTPZ is a conceptual zero-trust transmission protocol that combines FHE, ZKP, and E2EE to achieve end-to-end encryption from transmission to computation. FHE ensures end-to-end computational security, keeping the AI inference process in an encrypted state, constructing a “secure computing internet.”

4. Application Scenarios

DeFi Risk Control: Running risk control models on-chain in an encrypted manner to protect user data privacy.

Multi-party AI Training: Institutions encrypt and share data for collaborative model training on-chain.

Encrypted AI Assistant: User inquiries and AI inference are encrypted throughout, ensuring privacy.

5. Challenges and Trends

Challenges: FHE has slow computational performance, high development thresholds, and standardized protocols (such as HTTPZ) are still immature.

Trends: Projects like Zama and Aleo are promoting the application of FHE, and the DeCC framework is gradually improving.

Conclusion

FHE is the core engine of DeCC, constructing a trustless privacy computing network through universal computation in an encrypted state. It is not only the infrastructure for the integration of Web3 and AI but will also drive the future “intelligent and controllable” Agentic World, becoming the “operating system” of privacy computing.