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197
NonInteractive Verifiable Computing: Outsourcing Computation to Untrusted Workers
, 2009
"... Verifiable Computation enables a computationally weak client to “outsource ” the computation of a function F on various inputs x1,...,xk to one or more workers. The workers return the result of the function evaluation, e.g., yi = F(xi), as well as a proof that the computation of F was carried out co ..."
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Cited by 214 (12 self)
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Verifiable Computation enables a computationally weak client to “outsource ” the computation of a function F on various inputs x1,...,xk to one or more workers. The workers return the result of the function evaluation, e.g., yi = F(xi), as well as a proof that the computation of F was carried out correctly on the given value xi. The verification of the proof should require substantially less computational effort than computing F(xi) from scratch. We present a protocol that allows the worker to return a computationallysound, noninteractive proof that can be verified in O(m) time, where m is the bitlength of the output of F. The protocol requires a onetime preprocessing stage by the client which takes O(C) time, where C is the smallest Boolean circuit computing F. Our scheme also provides input and output privacy for the client, meaning that the workers do not learn any information about the xi or yi values. 1
Candidate indistinguishability obfuscation and functional encryption for all circuits
 In FOCS
, 2013
"... In this work, we study indistinguishability obfuscation and functional encryption for general circuits: Indistinguishability obfuscation requires that given any two equivalent circuits C0 and C1 of similar size, the obfuscations of C0 and C1 should be computationally indistinguishable. In functional ..."
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Cited by 169 (37 self)
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In this work, we study indistinguishability obfuscation and functional encryption for general circuits: Indistinguishability obfuscation requires that given any two equivalent circuits C0 and C1 of similar size, the obfuscations of C0 and C1 should be computationally indistinguishable. In functional encryption, ciphertexts encrypt inputs x and keys are issued for circuits C. Using the key SKC to decrypt a ciphertext CTx = Enc(x), yields the value C(x) but does not reveal anything else about x. Furthermore, no collusion of secret key holders should be able to learn anything more than the union of what they can each learn individually. We give constructions for indistinguishability obfuscation and functional encryption that supports all polynomialsize circuits. We accomplish this goal in three steps: • We describe a candidate construction for indistinguishability obfuscation for NC 1 circuits. The security of this construction is based on a new algebraic hardness assumption. The candidate and assumption use a simplified variant of multilinear maps, which we call Multilinear Jigsaw Puzzles. • We show how to use indistinguishability obfuscation for NC 1 together with Fully Homomorphic Encryption (with decryption in NC 1) to achieve indistinguishability obfuscation for all circuits.
Fully Homomorphic Encryption over the Integers
, 2009
"... We construct a simple fully homomorphic encryption scheme, using only elementary modular arithmetic. We use Gentry’s technique to construct fully homomorphic scheme from a “bootstrappable” somewhat homomorphic scheme. However, instead of using ideal lattices over a polynomial ring, our bootstrappabl ..."
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Cited by 138 (10 self)
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We construct a simple fully homomorphic encryption scheme, using only elementary modular arithmetic. We use Gentry’s technique to construct fully homomorphic scheme from a “bootstrappable” somewhat homomorphic scheme. However, instead of using ideal lattices over a polynomial ring, our bootstrappable encryption scheme merely uses addition and multiplication over the integers. The main appeal of our scheme is the conceptual simplicity. We reduce the security of our scheme to finding an approximate integer gcd – i.e., given a list of integers that are nearmultiples of a hidden integer, output that hidden integer. We investigate the hardness of this task, building on earlier work of HowgraveGraham.
Efficient Fully Homomorphic Encryption from (Standard) LWE
 LWE, FOCS 2011, IEEE 52ND ANNUAL SYMPOSIUM ON FOUNDATIONS OF COMPUTER SCIENCE, IEEE
, 2011
"... We present a fully homomorphic encryption scheme that is based solely on the (standard) learning with errors (LWE) assumption. Applying known results on LWE, the security of our scheme is based on the worstcase hardness of “short vector problems ” on arbitrary lattices. Our construction improves on ..."
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Cited by 117 (6 self)
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We present a fully homomorphic encryption scheme that is based solely on the (standard) learning with errors (LWE) assumption. Applying known results on LWE, the security of our scheme is based on the worstcase hardness of “short vector problems ” on arbitrary lattices. Our construction improves on previous works in two aspects: 1. We show that “somewhat homomorphic” encryption can be based on LWE, using a new relinearization technique. In contrast, all previous schemes relied on complexity assumptions related to ideals in various rings. 2. We deviate from the “squashing paradigm” used in all previous works. We introduce a new dimensionmodulus reduction technique, which shortens the ciphertexts and reduces the decryption complexity of our scheme, without introducing additional assumptions. Our scheme has very short ciphertexts and we therefore use it to construct an asymptotically efficient LWEbased singleserver private information retrieval (PIR) protocol. The communication complexity of our protocol (in the publickey model) is k · polylog(k) + log DB  bits per singlebit query (here, k is a security parameter).
Fully homomorphic encryption with relatively small key and ciphertext sizes
 In Public Key Cryptography — PKC ’10, Springer LNCS 6056
, 2010
"... Abstract. We present a fully homomorphic encryption scheme which has both relatively small key and ciphertext size. Our construction follows that of Gentry by producing a fully homomorphic scheme from a “somewhat ” homomorphic scheme. For the somewhat homomorphic scheme the public and private keys c ..."
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Cited by 115 (9 self)
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Abstract. We present a fully homomorphic encryption scheme which has both relatively small key and ciphertext size. Our construction follows that of Gentry by producing a fully homomorphic scheme from a “somewhat ” homomorphic scheme. For the somewhat homomorphic scheme the public and private keys consist of two large integers (one of which is shared by both the public and private key) and the ciphertext consists of one large integer. As such, our scheme has smaller message expansion and key size than Gentry’s original scheme. In addition, our proposal allows efficient fully homomorphic encryption over any field of characteristic two. 1
Functional Encryption: Definitions and Challenges
"... We initiate the formal study of functional encryption by giving precise definitions of the concept and its security. Roughly speaking, functional encryption supports restricted secret keys that enable a key holder to learn a specific function of encrypted data, but learn nothing else about the data. ..."
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Cited by 110 (17 self)
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We initiate the formal study of functional encryption by giving precise definitions of the concept and its security. Roughly speaking, functional encryption supports restricted secret keys that enable a key holder to learn a specific function of encrypted data, but learn nothing else about the data. For example, given an encrypted program the secret key may enable the key holder to learn the output of the program on a specific input without learning anything else about the program. We show that defining security for functional encryption is nontrivial. First, we show that a natural gamebased definition is inadequate for some functionalities. We then present a natural simulationbased definition and show that it (provably) cannot be satisfied in the standard model, but can be satisfied in the random oracle model. We show how to map many existing concepts to our formalization of functional encryption and conclude with several interesting open problems in this young area.
Computing arbitrary functions of encrypted data
 Commun. ACM
, 2010
"... Suppose that you want to delegate the ability to process your data, without giving away access to it. We show that this separation is possible: we describe a “fully homomorphic” encryption scheme that keeps data private, but that allows a worker that does not have the secret decryption key to comput ..."
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Cited by 80 (0 self)
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Suppose that you want to delegate the ability to process your data, without giving away access to it. We show that this separation is possible: we describe a “fully homomorphic” encryption scheme that keeps data private, but that allows a worker that does not have the secret decryption key to compute any (still encrypted) result of the data, even when the function of the data is very complex. In short, a third party can perform complicated processing of data without being able to see it. Among other things, this helps make cloud computing compatible with privacy. 1.
(Leveled) Fully Homomorphic Encryption without Bootstrapping
"... We present a novel approach to fully homomorphic encryption (FHE) that dramatically improves performance and bases security on weaker assumptions. A central conceptual contribution in our work is a new way of constructing leveled fully homomorphic encryption schemes (capable of evaluating arbitrary ..."
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Cited by 74 (9 self)
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We present a novel approach to fully homomorphic encryption (FHE) that dramatically improves performance and bases security on weaker assumptions. A central conceptual contribution in our work is a new way of constructing leveled fully homomorphic encryption schemes (capable of evaluating arbitrary polynomialsize circuits), without Gentry’s bootstrapping procedure. Specifically, we offer a choice of FHE schemes based on the learning with error (LWE) or Ring LWE (RLWE) problems that have 2λ security against known attacks. We construct: • A leveled FHE scheme that can evaluate depthL arithmetic circuits (composed of fanin 2 gates) using Õ(λ·L3) pergate computation. That is, the computation is quasilinear in the security parameter. Security is based on RLWE for an approximation factor exponential in L. This construction does not use the bootstrapping procedure. • A leveled FHE scheme that can evaluate depthL arithmetic circuits (composed of fanin 2 gates) using Õ(λ2) pergate computation, which is independent of L. Security is based on RLWE for quasipolynomial factors. This construction uses bootstrapping as an
Fully homomorphic encryption without modulus switching from classical GapSVP
 In Advances in Cryptology  Crypto 2012, volume 7417 of Lecture
"... We present a new tensoring technique for LWEbased fully homomorphic encryption. While in all previous works, the ciphertext noise grows quadratically (B → B 2 · poly(n)) with every multiplication (before “refreshing”), our noise only grows linearly (B → B · poly(n)). We use this technique to constr ..."
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Cited by 70 (5 self)
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We present a new tensoring technique for LWEbased fully homomorphic encryption. While in all previous works, the ciphertext noise grows quadratically (B → B 2 · poly(n)) with every multiplication (before “refreshing”), our noise only grows linearly (B → B · poly(n)). We use this technique to construct a scaleinvariant fully homomorphic encryption scheme, whose properties only depend on the ratio between the modulus q and the initial noise level B, and not on their absolute values. Our scheme has a number of advantages over previous candidates: It uses the same modulus throughout the evaluation process (no need for “modulus switching”), and this modulus can take arbitrary form. In addition, security can be classically reduced from the worstcase hardness of the GapSVP problem (with quasipolynomial approximation factor), whereas previous constructions could only exhibit a quantum reduction from GapSVP. Fully homomorphic encryption has been the focus of extensive study since the first candidate scheme was introduced by Gentry [Gen09b]. In a nutshell, fully homomorphic encryption allows to
Pinocchio: Nearly practical verifiable computation
 In Proceedings of the IEEE Symposium on Security and Privacy
, 2013
"... To instill greater confidence in computations outsourced to the cloud, clients should be able to verify the correctness of the results returned. To this end, we introduce Pinocchio, a built system for efficiently verifying general computations while relying only on cryptographic assumptions. With Pi ..."
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Cited by 64 (6 self)
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To instill greater confidence in computations outsourced to the cloud, clients should be able to verify the correctness of the results returned. To this end, we introduce Pinocchio, a built system for efficiently verifying general computations while relying only on cryptographic assumptions. With Pinocchio, the client creates a public evaluation key to describe her computation; this setup is proportional to evaluating the computation once. The worker then evaluates the computation on a particular input and uses the evaluation key to produce a proof of correctness. The proof is only 288 bytes, regardless of the computation performed or the size of the inputs and outputs. Anyone can use a public verification key to check the proof. Crucially, our evaluation on seven applications demonstrates that Pinocchio is efficient in practice too. Pinocchio’s verification time is typically 10ms: 57 orders of magnitude less than previous work; indeed Pinocchio is the first generalpurpose system to demonstrate verification cheaper than native execution (for some apps). Pinocchio also reduces the worker’s proof effort by an additional 1960×. As an additional feature, Pinocchio generalizes to zeroknowledge proofs at a negligible cost over the base protocol. Finally, to aid development, Pinocchio provides an endtoend toolchain that compiles a subset of C into programs that implement the verifiable computation protocol. 1