Ferret: Fast Extension for Correlated OT with Small Communication

Yang, Kang; Weng, Chenkai; Lan, Xiao; Zhang, Jiang; Wang, Xiao

doi:10.1145/3372297.3417276

Cited by 78 publications

(31 citation statements)

References 8 publications

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“…We provide concretely efficient protocols for 2-party circuit-PSI with linear computational and communication complexity that are up to 2.8× more performant than the state-of-the-art [43]. Both [43] and our protocols make use of IKNP style OT-Extension protocols [1,26,30,31], the concrete communication of which can be improved with the recent work on silent-OT extensions [5,51] as discussed in [5,16,48]. While the communication of these protocols is significantly lower, they are computationally more involved and hence their concrete performance depends on the network parameters.…”

Section: Discussionmentioning

confidence: 99%

Circuit-PSI With Linear Complexity via Relaxed Batch OPPRF

Chandran

Gupta

Shah

2021

Proceedings on Privacy Enhancing Technologies

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In 2-party Circuit-based Private Set Intersection (Circuit-PSI), P 0 and P 1 hold sets S0 and S1 respectively and wish to securely compute a function f over the set S0 ∩ S1 (e.g., cardinality, sum over associated attributes, or threshold intersection). Following a long line of work, Pinkas et al. (PSTY, Eurocrypt 2019) showed how to construct a concretely efficient Circuit-PSI protocol with linear communication complexity. However, their protocol requires super-linear computation. In this work, we construct concretely efficient Circuit-PSI protocols with linear computational and communication cost. Further, our protocols are more performant than the state-of-the-art, PSTY – we are ≈ 2.3× more communication efficient and are up to 2.8× faster. We obtain our improvements through a new primitive called Relaxed Batch Oblivious Programmable Pseudorandom Functions (RB-OPPRF) that can be seen as a strict generalization of Batch OPPRFs that were used in PSTY. This primitive could be of independent interest.

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Section: Discussionmentioning

confidence: 99%

Circuit-PSI With Linear Complexity via Relaxed Batch OPPRF

Chandran

Gupta

Shah

2021

Proceedings on Privacy Enhancing Technologies

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“…Due to the recent development of PCG-style OT extension protocols [132][133][134], these protocols outperform the IKNP-style OT extension protocols [113,130,135,136], and have the sublinear communication compared to the linear communication of the IKNP-style protocols (see Section 5 for more details). In this case, the efficiency improvement using the TinyKeys approach seems to be significantly smaller, if the recent PCG-style (instead of IKNP-style) OT extension protocols are adopted to construct the protocol Π semi Mult .…”

Section: Semi-honest Protocolsmentioning

confidence: 99%

“…Another style of OT extension protocols lies in the pseudorandom correlation generator (PCG) framework [162,254]. 3 In general, the PCG-style OT extension protocols [132,134,162,256] are able to generate COT correlations with sublinear communication (i.e., Õ( √ N ) for producing N COT correlations), but need more computation than IKNP-style protocols. To simplify the following description, we now give an informal definition of COT in a vector form.…”

Section: Oblivious Transfermentioning

confidence: 99%

Concretely efficient secure multi-party computation protocols: survey and more

Feng

Yang

2022

Security and Safety

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Secure multi-party computation (MPC) allows a set of parties to jointly compute a function on their private inputs, and reveals nothing but the output of the function. In the last decade, MPC has rapidly moved from a purely theoretical study to an object of practical interest, with a growing interest in practical applications such as privacy-preserving machine learning (PPML). In this paper, we comprehensively survey existing work on concretely efficient MPC protocols with both semi-honest and malicious security, in both dishonest-majority and honest-majority settings. We focus on considering the notion of security with abort, meaning that corrupted parties could prevent honest parties from receiving output after they receive output. We present high-level ideas of the basic and key approaches for designing different styles of MPC protocols and the crucial building blocks of MPC. For MPC applications, we compare the known PPML protocols built on MPC, and describe the efficiency of private inference and training for the state-of-the-art PPML protocols. Furthermore, we summarize several challenges and open problems to break though the efficiency of MPC protocols as well as some interesting future work that is worth being addressed. This survey aims to provide the recent development and key approaches of MPC to researchers, who are interested in knowing, improving, and applying concretely efficient MPC protocols.

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“…Recent works on silent-OT [22], [114] provide OT extensions with much lower communication than IKNP-style extensions [62], at the cost of higher computational overhead. Since our protocols make use of OTs in a black-box manner, silent-OT can be used to obtain lower communication.…”

Section: Other Related Workmentioning

confidence: 99%

SIRNN: A Math Library for Secure RNN Inference

Rathee¹,

Rathee²,

Goli³

et al. 2021

Preprint

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Complex machine learning (ML) inference algorithms like recurrent neural networks (RNNs) use standard functions from math libraries like exponentiation, sigmoid, tanh, and reciprocal of square root. Although prior work on secure 2party inference provides specialized protocols for convolutional neural networks (CNNs), existing secure implementations of these math operators rely on generic 2-party computation (2PC) protocols that suffer from high communication. We provide new specialized 2PC protocols for math functions that crucially rely on lookup-tables and mixed-bitwidths to address this performance overhead; our protocols for math functions communicate up to 423× less data than prior work. Some of the mixed bitwidth operations used by our math implementations are (zero and signed) extensions, different forms of truncations, multiplication of operands of mixed-bitwidths, and digit decomposition (a generalization of bit decomposition to larger digits). For each of these primitive operations, we construct specialized 2PC protocols that are more communication efficient than generic 2PC, and can be of independent interest. Furthermore, our math implementations are numerically precise, which ensures that the secure implementations preserve model accuracy of cleartext. We build on top of our novel protocols to build SIRNN, a library for end-to-end secure 2-party DNN inference, that provides the first secure implementations of an RNN operating on time series sensor data, an RNN operating on speech data, and a stateof-the-art ML architecture that combines CNNs and RNNs for identifying all heads present in images. Our evaluation shows that SIRNN achieves up to three orders of magnitude of performance improvement when compared to inference of these models using an existing state-of-the-art 2PC framework.Index Terms-privacy-preserving machine learning; secure two-party computation; recurrent neural networks; math functions; mixed-bitwidths; secure inference 1 We relegate comparisons with works that need additional parties for security, e.g., 3-party computation (3PC) to Section VII.

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Ferret: Fast Extension for Correlated OT with Small Communication

Cited by 78 publications

References 8 publications

Circuit-PSI With Linear Complexity via Relaxed Batch OPPRF

Circuit-PSI With Linear Complexity via Relaxed Batch OPPRF

Concretely efficient secure multi-party computation protocols: survey and more

SIRNN: A Math Library for Secure RNN Inference

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