Once upon a time, Princess Alice of the kingdom wanted to secretly send a scroll of magical formulas to the distant alchemist Bob but was worried that every mailman would peek at the scroll. Just as she fell into despair, a mysterious 'ciphertext mailman' appeared: he took Alice's scroll, sealed it into ciphertext, and quietly calculated the number of pages of the spell, added a timestamp, and even signed a credit certificate in encrypted form without unsealing it; only when it reached Bob's hands did he gently unseal it, resulting in a process that was completely consistent with the original plaintext operation, yet no one could see the secrets within. This mailman's miraculous skill is a true depiction of Fully Homomorphic Encryption (FHE).
Fully Homomorphic Encryption allows all operations to be completed in ciphertext state, resulting in decrypted values that are exactly the same as plaintext computation results, completely eliminating the risk of privacy leakage during processing; originally proposed by Craig Gentry in 2009, early implementations would slow down a Google search by a trillion times, but with technological evolution, today's performance overhead has been compressed to about a million times. In the future, this capability of 'one encryption, multiple computations' will fundamentally change the data processing model.
Meanwhile, Decentralized Confidential Computing (DeCC) is working through distributed nodes to enable secure computation of data even in any third-party or malicious environment, without the need for a centralized trusted party. DeCC is different from traditional blockchain privacy projects; it not only protects transaction privacy but also supports arbitrary encrypted computation of various logics; pioneers like iExec joined the Confidential Computing Alliance in 2019, laying the technical foundation and ecosystem for DeCC. Latest research has also combined confidential computing with decentralized artificial intelligence, achieving privacy protection for model inference in the Atoma network.
Moreover, technologies such as Multi-Party Computation (MPC) and Trusted Execution Environment (TEE) complement FHE, together constructing a more flexible and efficient privacy computing paradigm; the collaboration between Oasis and io.net is providing tools for encrypted AI inference and cross-chain asset exchange; Shade Protocol links encrypted smart contracts through TEE, ensuring data is never exposed in plaintext.
In terms of transmission, HTTPZ (Zero Trust Internet Transfer Protocol) is centered around FHE, creating a true 'zero trust' network protocol: all data, along with executable searches, filtering, and other operations, are completed on ciphertext, making it impossible for intermediate routes, caches, or even ISPs to decrypt or tamper with it; Mind Network has been the first to engineer HTTPZ for AI privacy computing, cross-chain secure transmission, gaming voting, and other scenarios.
Although FHE still faces challenges in computational efficiency, ciphertext expansion, standardization, and interoperability, its application threshold is rapidly decreasing with the collaborative optimization of hardware such as PIM accelerators, FPGA/ASICs, and the advancement of homomorphic encryption standardization alliances and NIST guidelines. In the future, FHE will become the core engine for decentralized confidential computing and zero trust transmission protocols, constructing a new paradigm in the digital world that truly combines security, privacy, and autonomy.
@mindnetwork_xyz, #MindNetwork全同态加密FHE重塑AI未来