Keyword Search and Oblivious Pseudorandom Functions

Freedman, Michael J.; Ishai, Yuval; Pinkas, Benny; Reingold, Omer

doi:10.1007/978-3-540-30576-7_17

Cited by 303 publications

(219 citation statements)

References 26 publications

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“…In the exact pattern matching setting, the algorithm of Freedman, Ishai, Pinkas and Reingold [13] achieves polylogarithmic overhead in m and n and polynomial overhead in security parameters in the honest-but-curious setting. Using efficient arguments [17,18] with the modern probabilistically checkable proofs (PCPs) of proximity [19], one can extend (at least asymptotically) their results to the malicious (static corruption) model.…”

Section: Comparison To Previous Workmentioning

confidence: 99%

“…Using efficient arguments [17,18] with the modern probabilistically checkable proofs (PCPs) of proximity [19], one can extend (at least asymptotically) their results to the malicious (static corruption) model. However, the protocol in [13] works only for exact matching and does not address more general problems, including singlecharacter wildcards and substring matching, which are the main focus of our work. Other protocols that address secure exact matching (and not wildcard or substring matching) are [12,20,21,22,23,11]; of these, only [22] obtains (full) security in the malicious setting.…”

Section: Comparison To Previous Workmentioning

confidence: 99%

“…Other protocols that address secure exact matching (and not wildcard or substring matching) are [12,20,21,22,23,11]; of these, only [22] obtains (full) security in the malicious setting. We note that [23] is more efficient than [13], but only in the random oracle model; here, we are interested in standard security models.…”

Section: Comparison To Previous Workmentioning

confidence: 99%

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5PM: Secure Pattern Matching

Baron

Defrawy

Minkovich

et al. 2012

Lecture Notes in Computer Science

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Abstract. In this paper we consider the problem of secure pattern matching that allows singlecharacter wildcards and substring matching in the malicious (stand-alone) setting. Our protocol, called 5PM, is executed between two parties: Server, holding a text of length n, and Client, holding a pattern of length m to be matched against the text, where our notion of matching is more general and includes non-binary alphabets, non-binary Hamming distance and non-binary substring matching.5PM is the first secure expressive pattern matching protocol designed to optimize round complexity by carefully specifying the entire protocol round by round. In the malicious model, 5PM requires O((m + n)k 2 ) bandwidth and O(m + n) encryptions, where m is the pattern length and n is the text length. Further, 5PM can hide pattern size with no asymptotic additional costs in either computation or bandwidth. Finally, 5PM requires only two rounds of communication in the honest-but-curious model and eight rounds in the malicious model. Our techniques reduce pattern matching and generalized Hamming distance problems to a novel linear algebra formulation that allows for generic solutions based on any additively homomorphic encryption. We believe our efficient algebraic techniques are of independent interest.

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Section: Comparison To Previous Workmentioning

confidence: 99%

Section: Comparison To Previous Workmentioning

confidence: 99%

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5PM: Secure Pattern Matching

Baron

Defrawy

Minkovich

et al. 2012

Lecture Notes in Computer Science

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“…It also appears likely to us that suitable VRFs could be a useful alternative in several applications which, as part of the system, output the value of the PRF together with a proof (interactive or non-interactive) that the evaluation was correct and has some additional properties. Examples of this include compact e-cash [11], keyword search [15], set intersection protocols [19], and adaptive oblivious transfer protocols [21].…”

Section: Related Workmentioning

confidence: 99%

Constructing Verifiable Random Functions with Large Input Spaces

Hohenberger

Waters

2010

Advances in Cryptology – EUROCRYPT 2010

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We present a family of verifiable random functions which are provably secure for exponentially-large input spaces under a non-interactive complexity assumption. Prior constructions required either an interactive complexity assumption or one that could tolerate a factor 2 n security loss for n-bit inputs. Our construction is practical and inspired by the pseudorandom functions of Naor and Reingold and the verifiable random functions of Lysyanskaya. Set in a bilinear group, where the Decisional DiffieHellman problem is easy to solve, we require the -Decisional Diffie-Hellman Exponent assumption in the standard model, without a common reference string. Our core idea is to apply a simulation technique where the large space of VRF inputs is collapsed into a small (polynomial-size) input in the view of the reduction algorithm. This view, however, is information-theoretically hidden from the attacker. Since the input space is exponentially large, we can first apply a collision-resistant hash function to handle arbitrarily-large inputs.

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“…The evaluation is oblivious in the sense that the party holding the key k does not learn x, while the other party only obtains FPRF(k, x) and has no knowledge of k [18], [19], [20].…”

Section: Oblivious Pseudo-random Function Evaluation (Oprf)mentioning

confidence: 99%

Secure computations on non-integer values

Franz

Deiseroth

Hamacher

et al. 2010

2010 IEEE International Workshop on Information Forensics and Security

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In this paper we present for the first time a framework that allows secure two-party computations on approximations of real valued signals. In our solution, we use a quantized logarithmic representation of the signal samples, which enables to represent both very small and very large numbers with bounded relative error. We show that numbers represented in this way can be encrypted using standard homomorphic encryption schemes; furthermore we give protocols that allow to perform all arithmetic operations on such encrypted values. Finally we demonstrate the practicality of our framework by applying it to the problem of filtering encrypted signals.

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Keyword Search and Oblivious Pseudorandom Functions

Cited by 303 publications

References 26 publications

5PM: Secure Pattern Matching

5PM: Secure Pattern Matching

Constructing Verifiable Random Functions with Large Input Spaces

Secure computations on non-integer values

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