• Publications
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ABY - A Framework for Efficient Mixed-Protocol Secure Two-Party Computation
TLDR
We introduce an abstract language that is compiled into a protocol representation, thereby relieving a developer from having to specify the functionality in the protocol’s (often complex) underlying representation. Expand
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Improved Garbled Circuit: Free XOR Gates and Applications
TLDR
We present a new garbled circuit construction for two-party secure function evaluation (SFE). Expand
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Secure Two-Party Computation is Practical
TLDR
In this paper we describe an implementation of the two-party case, using Yao's garbled circuits, and present various algorithmic protocol improvements. Expand
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TASTY: tool for automating secure two-party computations
TLDR
We present TASTY, a novel tool for automating, generating, executing, benchmarking, and comparing, efficient secure two-party computation protocols. Expand
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Improved Garbled Circuit Building Blocks and Applications to Auctions and Computing Minima
TLDR
We consider generic Garbled Circuit (GC)-based techniques for Secure Function Evaluation (SFE) in the semi-honest model. Expand
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Efficient Privacy-Preserving Face Recognition
TLDR
We present a privacy-preserving face recognition scheme that substantially improves over previouswork in terms of communication-and computation efficiency: the most recent proposal of Erkin et al. (PETS'09) requires O(log M) rounds to recognize a face in a database of M faces. Expand
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Chameleon: A Hybrid Secure Computation Framework for Machine Learning Applications
TLDR
We present Chameleon, a novel hybrid (mixed-protocol) framework for secure function evaluation (SFE) which enables two parties to jointly compute a function without disclosing their private inputs. Expand
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Ciphers for MPC and FHE
TLDR
We propose a new way of designing a cipher where most of the cryptographically relevant work would be performed as linear operations and the use of non-linear operations is minimized. Expand
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More efficient oblivious transfer and extensions for faster secure computation
TLDR
In this work we present optimizations and efficient implementations of OT and OT extensions in the semi-honest model and improve OT extensions with respect to communication complexity, computation complexity, and scalability. Expand
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Faster Private Set Intersection Based on OT Extension
TLDR
We give an overview on existing efficient PSI protocols that are secure against semi-honest adversaries. Expand
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