Secure two-party computations in ANSI C

By Andreas Holzer, Martin Franz, Stefan Katzenbeisser, Helmut Veith. 2012

145 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Hardware and Architecture

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Citations in the corpus

Pinocchio: Nearly Practical Verifiable Computation (2013, background): “These features (and limitations) are similar to a parallel effort [44] to compile C for the purposes of secure multiparty computation, though they compile only to Boolean circuits.”
Chameleon: A Hybrid Secure Computation Framework for Machine Learning Applications (2018, background): “The STP is instantiated as a separate compute node running a C/C++ implementation.”
Obliv-C: A Language for Extensible Data-Oblivious Computation (2015, methodology): “[10] attempted to leverage C in secure computation, but did not support most of the C language, while Obliv-C is a strict extension of C.”
More efficient oblivious transfer and extensions for faster secure computation (2013, unknown): “Due to many works that pushed secure computation further towards practical applications, e.g., [4, 5, 8, 11, 13, 21, 24, 30, 35–37, 44, 50], this conjecture has proven to be wrong and it is possible to carry out secure computation of complex functions at speeds that ﬁve years ago would have been…”
Combining Secret Sharing and Garbled Circuits for Efficient Private IEEE 754 Floating-Point Computations (2015, unknown): “State-of-the-art garbling methods are already very efficient [4] and, in addition, means to derive optimized circuits from existing programs have been developed [17][23].”
SoK: General Purpose Compilers for Secure Multi-Party Computation (2019, background): “Last major update EMP-toolkit [122] GC 2 09/2018 Obliv-C [129] GC 2 06/2018 ObliVM [97] GC 2 02/2016 TinyGarble [118] GC 2 10/2018 Wysteria [111] MC 2+ 10/2014 ABY [48] GC,MC 2 10/2018 SCALE-MAMBA - Hy 2+ 10/2018 Sharemind [24] Hy 3 09/2018 PICCO [134] Hy 3+ 10/2017 Frigate [101] 2+ - 05/2016 CBMC-G”
Two Halves Make a Whole - Reducing Data Transfer in Garbled Circuits Using Half Gates (2015, methodology): “The first implementation of secure two-party computation (2PC) [26] used Yao’s basic garbled circuit approach, and it remains the primary (but not only) paradigm for the many 2PC implementations that have been developed over the past ten years [10,12,14,21, 25,28].”
A Pragmatic Introduction to Secure Multi-Party Computation (2019, methodology): “To build CBMC-GC, Holzer et al. (2012) modified CBMC to output a Boolean circuit which can be then executed in circuit-based secure computation framework (such as the one from Huang et al. (2011b), which was used by CMBC-GC). Since CBMC was designed to optimize circuits for producing Boolean formula”
CrypTFlow: Secure TensorFlow Inference (2019, background): “There have been prior works that compile from lower-level, domain-speciﬁc languages to MPC. Examples include Fairplay [43], Wysteria [53], ObliVM [41], CBMC-GC [32], SMCL [49], Sharemind [13], EzPC [17], SPDZ [7], and HyCC [15].”
GraphSC: Parallel Secure Computation Made Easy (2015, background): “Section IV and Figure 5 later in the paper will elaborate on the details of our models and terminology.”
Compacting privacy-preserving k-nearest neighbor search using logic synthesis (2015, methodology): “In the area of mapping and optimizing functions into Boolean logic for GC, the related literature has suggested developing custom compilers [9,11,19,23], custom libraries for conventional high-level compilers [10, 14, 22], hardware accelerators[2, 16,27], and mobile device implementation [24].”