Efficient RSA Key Generation and Threshold Paillier in the Two-Party Setting

Hazay, Carmit; Mikkelsen, Gert Læssøe; Rabin, Tal; Toft, Tomas

doi:10.1007/978-3-642-27954-6_20

Cited by 68 publications

(66 citation statements)

References 55 publications

(54 reference statements)

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“…Hazay et al presented a threshold Paillier encryption scheme for two-party setting, and a protocol for generating an RSA composite [26].…”

Section: Related Workmentioning

confidence: 99%

“…The Paillier scheme is a probabilistic public-key encryption scheme [13,26,35], which works as follows. A node i encrypts its private value xi using the encryption function E and the public key.…”

Section: Homomorphic Encryptionmentioning

confidence: 99%

“…In particular, we focus on the secure sum aggregation. Among all secure computation schemes, we evaluate three representative groups: secret sharing [7,39], homomorphic encryption [2,26,35,40], and perturbation-based [11]. They represent different approaches of ensuring security: splitting data into shares (secret sharing), encrypting data (homomorphic encryption), and perturbing data with significant noise (perturbation-based).…”

Section: Introductionmentioning

confidence: 99%

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Secure multiparty aggregation with differential privacy

Goryczka

Xiong

Sunderam

2013

Proceedings of the Joint EDBT/ICDT 2013 Workshops

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This paper considers the problem of secure data aggregation in a distributed setting while preserving differential privacy for the aggregated data. In particular, we focus on the secure sum aggregation. Security is guaranteed by secure multiparty computation protocols using well known security schemes: Shamir's secret sharing, perturbation-based, and various encryption schemes. Differential privacy of the final result is achieved by distributed Laplace perturbation mechanism (DLPA). Partial random noise is generated by all participants, which draw random variables from Gamma or Gaussian distributions, such that the aggregated noise follows Laplace distribution to satisfy differential privacy. We also introduce a new efficient distributed noise generation scheme with partial noise drawn from Laplace distributions.We compare the protocols with different privacy mechanisms and security schemes in terms of their complexity and security characteristics. More importantly, we implemented all protocols, and present an experimental comparison on their performance and scalability in a real distributed environment.

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“…Hazay et al presented a threshold Paillier encryption scheme for two-party setting, and a protocol for generating an RSA composite [26].…”

Section: Related Workmentioning

confidence: 99%

Section: Homomorphic Encryptionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Secure multiparty aggregation with differential privacy

Goryczka

Xiong

Sunderam

2013

Proceedings of the Joint EDBT/ICDT 2013 Workshops

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“…For Paillier one can use the protocol of [HMRT12] for which its efficiency is dominated by the number of trial divisions for testing the candidates composites. This protocol ensures an improved analysis based on the analysis from [BF01] for which a random number of length 1024 is a prime with probability 1/44, condition that it passed a trial division with some threshold parameter B.…”

Section: Properties Of Homomorphic Pkementioning

confidence: 99%

“…For the Paillier encryption scheme we get that coming up with a polynomial Q(·) and y such that Q(y) ∈ Z * N amounts to factoring the product N . The public key generation can be computed using the efficient protocol of Hazay et al [HMRT12] that is proven with simulation based security in the malicious setting. To the best of our knowledge, this is the only non-generic protocol that guarantees simulation based security in the two-party setting.…”

Section: Security In the Presence Of Malicious Adversariesmentioning

confidence: 99%

Efficient Set Intersection with Simulation-Based Security

et al. 2014

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We consider the problem of computing the intersection of private datasets of two parties, where the datasets contain lists of elements taken from a large domain. This problem has many applications for online collaboration. In this work we present protocols based on the use of homomorphic encryption and different hashing schemes for both the semi-honest and malicious environments. The protocol for the semi-honest environment is secure in the standard model, while the protocol for the malicious environment is secure in the random oracle model. Our protocols obtain linear communication and computation overhead. We further implement different variants of our semi-honest protocol. Our experiments show that the asymptotic overhead of the protocol is affected by different constants. (In particular, the degree of the polynomials evaluated by the protocol matters less than the number of polynomials that are evaluated.) As a result, the protocol variant with the best asymptotic overhead is not necessarily preferable for inputs of reasonable size.

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Secure similarity coefficients computation for binary data and its extensions

Zhang

2013

Concurrency and Computation

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SUMMARYSimilarity measures play an important role in classification problems, cluster analysis, and identification issues. This paper studies the secure similarity coefficients computation in the two‐party setting. Recently, a privacy‐preserving similarity coefficients protocol for binary data was proposed by Wong and Kim (Computers and Mathematics with Application 2012). We point out that their protocol is not secure, even in the semi‐honest model. In their protocol, the client can retrieve the inputs of the server without deviating from the protocol. Next, we propose a secure similarity coefficients computation protocol in the presence of malicious adversaries, which solves the same similarity coefficients functionality as that proposed by Wong and Kim. Meanwhile, we prove the protocol secure against the malicious adversaries by using the standard simulation‐based security definitions for secure two‐party computation. Also several extensions of our protocol for settling other specific problems are discussed. At last, we present a protocol computing the similarity coefficients with better privacy by using the secure integer division on ciphertexts. Copyright © 2013 John Wiley & Sons, Ltd.

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Efficient RSA Key Generation and Threshold Paillier in the Two-Party Setting

Cited by 68 publications

References 55 publications

Secure multiparty aggregation with differential privacy

Secure multiparty aggregation with differential privacy

Efficient Set Intersection with Simulation-Based Security

Secure similarity coefficients computation for binary data and its extensions

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