Verified80% confidenceTradeoffExact time
Homomorphic 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.
4
Sources
80%
Confidence
Long-term
Relevance
8/29/2026
First Seen
Sources
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Related Claims
UnverifiedHomomorphic 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.79% 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74% similarUnverifiedThe security of modern cryptographic systems is built on the assumption that certain mathematical problems are 'computationally infeasible,' such as large integer factorization and discrete logarithm solving.74% similarUnverifiedThe computational overhead of more advanced approaches such as differential privacy or homomorphic encryption is currently difficult to apply to real-time conversational scenarios.74% similarUnverifiedTraditional 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.74% similar
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