In the future 'Agentic World', millions of AI agents will collaborate to drive innovation in fields such as healthcare, finance, and gaming. However, as data becomes the currency of the new era, how can privacy, security, and verifiability be ensured? Fully Homomorphic Encryption (FHE), as a groundbreaking technology, provides a solid security infrastructure for the development of AI and reshapes our understanding of data, identity, and trust. This article will explore how FHE empowers AI and plays a central role in a decentralized world.
FHE: A Revolutionary Technology for AI Security
Fully Homomorphic Encryption allows computations to be performed directly on encrypted data without the need for decryption. This means that sensitive data can be processed and analyzed without exposing the original information. For AI, the application scenarios of this technology are ubiquitous:
1. Healthcare Sector: Medical data is highly sensitive, and FHE enables AI models to make diagnostic predictions on encrypted patient data. For example, hospitals can share encrypted data to train federated learning models without worrying about privacy leaks, thus accelerating drug development and personalized treatment.
2. DeFi (Decentralized Finance): In DeFi, FHE can protect users' transaction records and asset data while allowing smart contracts to perform complex computations on encrypted data. For example, lending protocols can verify credit scores without exposing users' financial situations.
3. Gaming and the Metaverse: In decentralized gaming, FHE ensures the privacy of player data (such as asset ownership and game progress) while supporting real-time encrypted computations to prevent cheating, creating a fair gaming environment.
How does FHE empower AI agents?
In the Agentic World, AI agents need to have capabilities such as identity identification, secure environments, decentralized computing, and data protection. FHE provides critical support for these needs:
- Identity and Authorization: FHE allows AI agents to verify their permissions without exposing user identities. For example, users can authorize AI to access their social preference data, but through FHE, the data remains encrypted at all times, ensuring that only authorized computation results are shared.
- Secure Environment: FHE provides agents with a 'zero trust' computing environment, where no third party (including the AI itself) can directly access the original data. This is crucial for preventing data misuse.
- Decentralization and Verifiable Computing: Combined with blockchain, FHE supports Decentralized Confidential Computing (DeCC). Agents can perform encrypted computations in multi-party collaborations, with results verifiable through blockchain, ensuring transparency and trustworthiness.
The Fusion of AI and Blockchain: The Key Role of FHE
The combination of AI and blockchain is driving the development of multi-chain collaboration and consensus mechanisms among agents. FHE plays a core role as a secure infrastructure in the following aspects:
1. Multi-Chain Collaboration: In cross-chain scenarios, FHE ensures the privacy of data when transmitted between different blockchains. For example, medical AI can obtain encrypted data from multiple blockchains for joint analysis without exposing any party's data.
2. Consensus Among Agents: FHE supports consensus mechanisms under encrypted conditions. AI agents can reach consensus on computation results without sharing original data, which is essential for decentralized markets, supply chains, and other scenarios.
3. The Necessity of End-to-End Encryption: In the future zero trust internet (HTTPZ), end-to-end encryption is a fundamental requirement. FHE not only protects data transmission but also safeguards the data processing process, ensuring complete security from input to output.
Would you allow AI to access your data?
A question worth pondering: Would you allow AI to access your identity, transaction records, or social preferences? The answer often depends on 'trust'. FHE enables users to selectively share information without exposing complete data through an encrypted authorization mechanism. For example, on social platforms, FHE can allow AI to generate personalized recommendations based on encrypted user preferences without knowing the specific preference content. This 'minimized data exposure' model returns control of data back to users.
FHE and Future Vision: DeCC and HTTPZ
FHE is not only the technical pillar of AI but also the core of Decentralized Confidential Computing (DeCC) and the Zero Trust Internet Protocol (HTTPZ). DeCC utilizes FHE to achieve encrypted computations for multi-party collaboration, suitable for supply chain management, cross-organizational data sharing, and other scenarios. Meanwhile, HTTPZ relies on FHE to create a fully encrypted internet, where data is protected throughout its transmission and processing, achieving true 'zero trust.'
FHE Reshaping the Foundation of AI's Future
In the Agentic World, FHE is not just a technical tool, but the cornerstone of trust. It provides AI agents with a secure, decentralized, and verifiable computing environment, promoting the application of AI in healthcare, DeFi, gaming, and more. Through its integration with blockchain, FHE will accelerate the future of AI and multi-chain collaboration, achieving a perfect balance of data privacy and value.
Let us look forward to how FHE will reshape the infinite possibilities of AI in the future decentralized world!
