STOC '87 Proceedings of the nineteenth annual ACM symposium on Theory of computing
Founding crytpography on oblivious transfer
STOC '88 Proceedings of the twentieth annual ACM symposium on Theory of computing
Non-interactive oblivious transfer and applications
CRYPTO '89 Proceedings on Advances in cryptology
A minimal model for secure computation (extended abstract)
STOC '94 Proceedings of the twenty-sixth annual ACM symposium on Theory of computing
Oblivious transfer and polynomial evaluation
STOC '99 Proceedings of the thirty-first annual ACM symposium on Theory of computing
A Pseudorandom Generator from any One-way Function
SIAM Journal on Computing
The Decision Diffie-Hellman Problem
ANTS-III Proceedings of the Third International Symposium on Algorithmic Number Theory
Non-Interactive CryptoComputing For NC1
FOCS '99 Proceedings of the 40th Annual Symposium on Foundations of Computer Science
FOCS '00 Proceedings of the 41st Annual Symposium on Foundations of Computer Science
Noisy polynomial interpolation and noisy chinese remaindering
EUROCRYPT'00 Proceedings of the 19th international conference on Theory and application of cryptographic techniques
Oblivious neural network computing via homomorphic encryption
EURASIP Journal on Information Security
Secure multiparty computation between distrusted networks terminals
EURASIP Journal on Information Security
Anonymous biometric access control
EURASIP Journal on Information Security - Special issue on enhancing privacy protection in multimedia systems
Privacy-preserving back-propagation and extreme learning machine algorithms
Data & Knowledge Engineering
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We study the problem of oblivious polynomial evaluation (OPE). There are two parties, Alice who has a polynomial P, and Bob who has an input x. The goal is for Bob to compute P(x) in such a way that Alice learns nothing about x and Bob learns only what can be inferred from P(x). Previously existing protocols were based on some newly-invented intractability assumptions that have not been well studied, so one may have doubts about the security of these protocols. In this paper, we propose OPE protocols which are only based on the standard primitive oblivious transfer, and still our protocols are more efficient in several natural cases. Our protocols can also be easily modified to handle multivariate polynomials and polynomials over floating-point numbers. As an application, we study the problem of oblivious neural learning, where one party has a neural network and the other, with some training set, wants to train the neural network in an oblivious way. We provide a protocol for this problem, which is based on our protocol for OPE.