Method evidence record

Homomorphic Encryption

Homomorphic Encryption (HE) is a cryptographic framework that allows arbitrary computations to be performed directly on encrypted data without requiring decryption. First realized as a fully general construction by Craig Gentry in 2009 using ideal lattices, it enables a server to process sensitive data and return an encrypted result that, when decrypted by the data owner, equals the result of performing the same computation on the plaintext. It is foundational to privacy-preserving machine learning, secure cloud computing, and confidential analytics.

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Fully Homomorphic Encryption

Taxonomic method record · ml-model / privacy

Gentry, C. (2009). Fully homomorphic encryption using ideal lattices. ACM Symposium on Theory of Computing (STOC), 169–178. · DOI 10.1145/1536414.1536440

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Related methods

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Same method familyDifferential Privacymachine-suggested · Relational suggestion, not evidence.Same method familyFederated Learningmachine-suggested · Relational suggestion, not evidence.Same method familySecure Multi-Party Computationmachine-suggested · Relational suggestion, not evidence.