Unverified50% confidenceFactExact time
Traditional multi-party computation (MPC) is implemented through cryptographic protocols such as secret sharing and homomorphic encryption, but the computational overhead is enormous, making it difficult to apply to large-scale neural network inference.
1
Sources
50%
Confidence
Long-term
Relevance
9/22/2026
First Seen
Sources
Related Entities
Related Claims
VerifiedHomomorphic encryption theoretically allows inference to be run directly on encrypted data, but the computational overhead is still too large and it has not yet become practical.74% similarUnverifiedHomomorphic encryption allows computations to be performed directly on encrypted data, its mathematical foundation is built on lattice-based cryptography, and it has now advanced to fourth-generation schemes (such as CKKS and BFV), but computational overhead remains thousands to millions of times that of plaintext computation.70% similarUnverifiedThe computational overhead of more advanced approaches such as differential privacy or homomorphic encryption is currently difficult to apply to real-time conversational scenarios.69% similarUnverified在密文上做运算的计算量往往是明文运算的成千上万倍，是同态加密工程化的最大障碍68% similarUnverifiedIn envelope encryption, the encryption of large volumes of data is performed locally by the Data Key at high speed, and interaction with external services is limited to encrypting and decrypting the extremely small Data Key, thereby controlling network overhead and latency.68% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/941628API
curl https://kongchang.com/api/v1/knowledge/claims/941628MCP
get_claim(id=941628)