With the evolution of AI Agents, everyone may have a 'digital double' in the future to automatically perform tasks, manage assets, or even collaborate with other intelligent entities. However, without identity verification, secure execution, privacy protection, and decentralized trust mechanisms, these Agents are easily preyed upon by hackers and centralized platforms. This is precisely the moment when FHE (Fully Homomorphic Encryption) plays the role of a savior.
FHE is like equipping the AI Agent with a full set of encrypted armor, enhancing its autonomy and credibility in an open environment across all dimensions from identity to data, from computation to interaction.
1. FHE creates the Agent's 'encrypted identity system': Who am I? Who is me?
In an environment without a trust center, how does the Agent prove that it 'is itself'? FHE can be used to build an encrypted identity verification mechanism:
The Agent's identity authentication logic (such as biometric features, key signatures) can be encrypted to prevent exposure of plaintext information and identity theft.
Using FHE, the Agent can determine or sign identity features through AI models without disclosing identity information, achieving 'privacy verification'.
Result: Authentication does not require trust in third parties, privacy and autonomy coexist.
2. Secure execution environment: The Agent's brain has a 'firewall'.
AI Agents need to handle a large number of tasks, such as on-chain signatures, asset management, contract execution, etc. Using traditional encryption methods, once computation is needed, decryption must occur, exposing risks. FHE supports:
End-to-end encrypted execution: The Agent's brain can handle encrypted tasks without needing to decrypt data.
Intrusion-resistant design: Even if the operating system or hardware is compromised, data and tasks in an encrypted state cannot be leaked.
Result: Even if you invade the Agent, you cannot see what it is doing.
3. Decentralized collaboration: The Agent's 'encrypted social network'.
Future Agents will be interconnected to collaboratively complete complex tasks. FHE assists:
Trustless multi-Agent collaboration: Multiple Agents collaborate through FHE encryption protocols, each computing part of the tasks without sharing plaintext data.
Cross-platform execution assurance: Agents running on-chain or off-chain platforms can use FHE for secure collaboration, without relying on centralized nodes.
Result: Agents combine freely, forming alliances without worrying about 'traitors' or 'eavesdroppers'.
4. Verifiable computation: What I did, you can confidently verify!
To establish trust, the Agent's behavior must be verifiable. FHE combined with ZKP (Zero-Knowledge Proof) can achieve:
Computation is not exposed, results can be verified: even if the process is completely encrypted, others can verify whether the results are legitimately generated by the Agent.
On-chain trusted execution record: Write on-chain through FHE + ZK, ensuring the authenticity and privacy of each Agent's actions.
Result: Under privacy, it can still achieve 'You can rest assured with what I do.'
5. Data protection: The Agent's memory is no longer 'exposed'.
AI Agents need to handle sensitive content such as user behavior, asset information, and preference data, which are precisely the areas FHE excels at protecting:
Data exists encrypted throughout its lifecycle, and there is no need to decrypt even during use.
The Agent can train models and make decisions from multiple privacy sources, and user data never leaves the 'shell'.
Result: Your data has become the Agent's 'secret manual', but no one can steal it.
Conclusion: FHE is the 'soul anchor' of AI Agents.
An Agent without FHE is like a shelled egg or a naked neural network, neither trustworthy nor secure. The five pillars that FHE provides for Agents—identity, environment, collaboration, verification, and data—will be the key foundation for truly becoming 'intelligent individuals'.
If AI is the body of the Agent, then FHE is the core soul that makes it an 'encrypted super body'. As FHE technology accelerates towards practical use, this transition from 'human-controlled AI' to 'AI autonomy' is waiting for us not far ahead.
