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Lecture notes in computer science

Practical Secure Evaluation of Semi-private Functions

Annika Paus, Ahmad‐Reza Sadeghi, Thomas H. Schneider

Published Jan 1, 2009• 71 citations
Publisher
DOI
10.1007/978-3-642-01957-9_6

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This thesis focuses on practical aspects of general two-party Secure Function Evaluation (SFE). We give a new SFE protocol that allows free evaluation of XOR gates and is provably secure against semi-honest adversaries in the random oracle model. Furthermore, the extension of SFE to private functions (PF-SFE) using universal circuits (UC) is considered. Based on our new practical UC construction, FairplayPF is implemented as extension of the well-known Fairplay SFE system to demonstrate practicability of UC-based PF-SFE. Also new protocols for SFE and PF-SFE of functions alternatively represented as Ordered Binary Decision Diagram (OBDD) are given.

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Outsourcing computation for private function evaluation

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Outsourced secure multiparty computation (SMC) protocols allow resource-constrained devices to execute input-private computation with great efficiency. Unfortunately, existing outsourced SMC protocols require that all parties know the function being evaluated, precluding applications where the function itself must remain private. We develop the first linear-complexity protocols for outsourcing private function evaluation (PFE), SMC protocols that provide input and function privacy. Assuming a semi-honest function holder, we build on existing two-party PFE constructions to develop outsourced protocols that are secure against a semi-honest, covert, or malicious outsourcing server and malicious mobile participants. To do this, we develop a garbling technique for combining public and private sub-circuits in a single computation. This allows us to apply auxiliary checks for malicious behaviour using only free-XOR gates. These protocols demonstrate the feasibility of outsourced PFE and provide a first step towards privacy-preserving applications for use in cloud computing.

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Generalizing Semi-Private Function Evaluation

Bieber, Julian

The cryptographic primitive Secure Function Evaluation (SFE) enables the evaluation of a function public function f (x, y), under input parameters that are provided by different parties without them revealing their specific value.Restricting SFE further by requiring the function to be only known by one party is called Private Function Evaluation (PFE).Furthermore Semi-Private Function Evaluation (SPF-SFE) can help to increase the maximum function size which can be evaluated in a somewhat private manner.One way to achieve SPF-SFE is to split the function into blocks, as was shown in [PSS09].However their implementation was crafted specifically for Yao's garbled Circuit protocol.Therefore there are protocols, namely Goldreich-Micali-Wigderson (GMW), by which it could not be evaluated.We provide circuit designs for different Privately Programmable Blocks, which are constructed to work with the GMW protocol as well.Additionally we provide a toolchain to achieve SPF-SFE efficiently.Furthermore we implemented a tool used in the toolchain, which uses the aforementioned designs and can combine them with plain circuits and Universal Circuits (UCs) to build a single programmable circuit.A function designer can use the toolchain to balance out his needs for function privacy with performance.Contents 5.2.4 Combined Circuits . . .

•Oct 1, 2016•0 citations
This thesis focuses on practical aspects of general two-party Secure Function Evaluation (SFE). We give a new SFE protocol that allows free evaluation of XOR gates and is provably secure against semi-honest adversaries in the random oracle model. Furthermore, the extension of SFE to private functions (PF-SFE) using universal circuits (UC) is considered. Based on our new practical UC construction, FairplayPF is implemented as extension of the well-known Fairplay SFE system to demonstrate practicability of UC-based PF-SFE. Also new protocols for SFE and PF-SFE of functions alternatively represented as Ordered Binary Decision Diagram (OBDD) are given.
Outsourced secure multiparty computation (SMC) protocols allow resource-constrained devices to execute input-private computation with great efficiency. Unfortunately, existing outsourced SMC protocols require that all parties know the function being evaluated, precluding applications where the function itself must remain private. We develop the first linear-complexity protocols for outsourcing private function evaluation (PFE), SMC protocols that provide input and function privacy. Assuming a semi-honest function holder, we build on existing two-party PFE constructions to develop outsourced protocols that are secure against a semi-honest, covert, or malicious outsourcing server and malicious mobile participants. To do this, we develop a garbling technique for combining public and private sub-circuits in a single computation. This allows us to apply auxiliary checks for malicious behaviour using only free-XOR gates. These protocols demonstrate the feasibility of outsourced PFE and provide a first step towards privacy-preserving applications for use in cloud computing.
The cryptographic primitive Secure Function Evaluation (SFE) enables the evaluation of a function public function f (x, y), under input parameters that are provided by different parties without them revealing their specific value.Restricting SFE further by requiring the function to be only known by one party is called Private Function Evaluation (PFE).Furthermore Semi-Private Function Evaluation (SPF-SFE) can help to increase the maximum function size which can be evaluated in a somewhat private manner.One way to achieve SPF-SFE is to split the function into blocks, as was shown in [PSS09].However their implementation was crafted specifically for Yao's garbled Circuit protocol.Therefore there are protocols, namely Goldreich-Micali-Wigderson (GMW), by which it could not be evaluated.We provide circuit designs for different Privately Programmable Blocks, which are constructed to work with the GMW protocol as well.Additionally we provide a toolchain to achieve SPF-SFE efficiently.Furthermore we implemented a tool used in the toolchain, which uses the aforementioned designs and can combine them with plain circuits and Universal Circuits (UCs) to build a single programmable circuit.A function designer can use the toolchain to balance out his needs for function privacy with performance.Contents 5.2.4 Combined Circuits . . .