Compiling Low Depth Circuits for Practical Secure Computation

Buescher, Niklas; Holzer, Andreas; Weber, Alina; Katzenbeisser, Stefan

doi:10.1007/978-3-319-45741-3_5

Cited by 25 publications

(21 citation statements)

References 29 publications

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“…Our work on hybrid compilation is built on top of the compiler CBMC-GC [26], which provides a tool-chain from a (comparably) high-level language, i.e., ANSI C, to Boolean circuits. CBMC-GC has recently been extended to not only optimize circuits for size, described in [8], but also for depth [9], which jointly with its powerful symbolic execution, makes it a perfect candidate for hybrid compilation. Building on top of CBMC-GC, HyCC considers the complete input code as private functionality, i.e., public computations that are performed locally by each party are not supported.…”

Section: The Cbmc-gc Compilermentioning

confidence: 99%

“…The different modules identified in the previous step are compiled separately into two or three circuit representations. Namely, every module is compiled into size-optimized Boolean circuits using the circuit compiler of CBMC-GC and into depth-optimized Boolean circuits using its ShallowCC extension [9], which uses depth-optimized building blocks (cf. §2.4).…”

Section: Circuit Compilationmentioning

confidence: 99%

“…Previous MPC compilers either only targeted a single class of protocols, e.g., Yao's garbled circuits [26,39,48], the GMW protocol [9,17], or linear secret-sharing-based MPC [7], or the compilers required the developer to use specific annotations to mark which protocol is used for each statement, e.g., [18,24]. The only other compiler that addresses the compilation of a program using two MPC protocols (Yao's gabled circuits and arithmetic sharing) is EzPC [14].…”

Section: Introductionmentioning

confidence: 99%

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HyCC

Büscher

Demmler

Katzenbeisser

et al. 2018

Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security

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While secure multi-party computation (MPC) is a vibrant research topic and a multitude of practical MPC applications have been presented recently, their development is still a tedious task that requires expert knowledge. Previous works have made first steps in compiling high-level descriptions from various source descriptions into MPC protocols, but only looked at a limited set of protocols. In this work we present HyCC, a tool-chain for automated compilation of ANSI C programs into hybrid protocols that efficiently and securely combine multiple MPC protocols with optimizing compilation, scheduling, and partitioning. As a result, our compiled protocols are able to achieve performance numbers that are comparable to hand-built solutions. For the MiniONN neural network (Liu et al., CCS 2017), our compiler improves performance of the resulting protocol by more than a factor of 3. Thus, for the first time, highly efficient hybrid MPC becomes accessible for developers without cryptographic background.

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Section: The Cbmc-gc Compilermentioning

confidence: 99%

Section: Circuit Compilationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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HyCC

Büscher

Demmler

Katzenbeisser

et al. 2018

Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security

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“…In order to find the user's coordinates in Privacy-Preserving Indoor Localization (PPIL), we have to find the coordinates that correspond to the nearest Reference Points (RPs) by their secret-shared indices computed by the k-NN algorithm. We use an approach similar to the one proposed by Keller and Scholl [100] for our size-optimized implementation, and design a new Single Instruction Multiple Data (SIMD) capable circuit for the depth-optimized implementation with the same AND-depth and slightly larger AND-size than the circuit proposed by Buescher et al [101] (the latter cannot be parallelized easily with SIMD).…”

Section: Oblivious Array Accessmentioning

confidence: 99%

“…8 in §A. In contrast to the circuits of Buescher et al [101], our Oblivious Array Access (OA) circuit is slightly larger, but it has a much simpler structure and therefore the same subcircuits can be applied in parallel using SIMD.…”

Section: Oblivious Array Accessmentioning

confidence: 99%

PILOT: Practical Privacy-Preserving Indoor Localization Using OuTsourcing

Järvinen

Leppäkoski

Lohan

et al. 2019

2019 IEEE European Symposium on Security and Privacy (EuroS&P)

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In the last decade, we observed a constantly growing number of Location-Based Services (LBSs) used in indoor environments, such as for targeted advertising in shopping malls or finding nearby friends. Although privacy-preserving LBSs were addressed in the literature, there was a lack of attention to the problem of enhancing privacy of indoor localization, i.e., the process of obtaining the users' locations indoors and, thus, a prerequisite for any indoor LBS.In this work we present PILOT, the first practically efficient solution for Privacy-Preserving Indoor Localization (PPIL) that was obtained by a synergy of the research areas indoor localization and applied cryptography. We design, implement, and evaluate protocols for Wi-Fi fingerprint-based PPIL that rely on 4 different distance metrics. To save energy and network bandwidth for the mobile end devices in PPIL, we securely outsource the computations to two non-colluding semi-honest parties. Our solution mixes different secure two-party computation protocols and we design size-and depth-optimized circuits for PPIL. We construct efficient circuit building blocks that are of independent interest: Single Instruction Multiple Data (SIMD) capable oblivious access to an array with low circuit depth and selection of the k-Nearest Neighbors with small circuit size. Additionally, we reduce Received Signal Strength (RSS) values from 8 bits to 4 bits without any significant accuracy reduction. Our most efficient PPIL protocol is 553x faster than that of Li et al. (INFOCOM'14) and 500x faster than that of Ziegeldorf et al. (WiSec'14). Our implementation on commodity hardware has practical run-times of less than 1 second even for the most accurate distance metrics that we consider, and it can process more than half a million PPIL queries per day. 448 2019 IEEE European Symposium on Security and Privacy (EuroS&P)

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