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Or Weinstein

dblp:187/5510 · DBLP profile ↗
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3ranked-venue papers
0as first author
1since 2021 · last 2023
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Security and privacy · 3 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Network and information security
3 papers
Cryptographic protocols and secure computation · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Cryptographic protocols and secure computation
secure multiparty computation
1.232023
High-Throughput Secure Three-Party Computation with an Honest Majority · J. Cryptol. 2023
Optimized Honest-Majority MPC for Malicious Adversaries - Breaking the 1 Billion-Gate Per Second Barrier · IEEE Symposium on Security and Privacy 2017
High-Throughput Secure Three-Party Computation for Malicious Adversaries and an Honest Majority · EUROCRYPT (2) 2017
Cryptographic protocols and secure computation › secure multiparty computation
three-party computation
0.922023
High-Throughput Secure Three-Party Computation with an Honest Majority · J. Cryptol. 2023
High-Throughput Secure Three-Party Computation for Malicious Adversaries and an Honest Majority · EUROCRYPT (2) 2017
Cryptographic protocols and secure computation › secure multiparty computation › secure two-party computation
cut-and-choose
0.112017
Optimized Honest-Majority MPC for Malicious Adversaries - Breaking the 1 Billion-Gate Per Second Barrier · IEEE Symposium on Security and Privacy 2017
Cryptographic protocols and secure computation
malicious security
0.112017
High-Throughput Secure Three-Party Computation for Malicious Adversaries and an Honest Majority · EUROCRYPT (2) 2017

Methods — techniques the papers use, named apart from their topics

secret sharing · 0.7honest majority · 0.7multiplication triples · 0.3cut-and-choose · 0.3cache-efficient shuffling · 0.3
YearPublicationVenuePosition
2023 High-Throughput Secure Three-Party Computation with an Honest Majority
Jun Furukawa 0001, Yehuda Lindell, Ariel Nof, Or Weinstein
J. Cryptol.4
2017 High-Throughput Secure Three-Party Computation for Malicious Adversaries and an Honest Majority
Jun Furukawa 0001, Yehuda Lindell, Ariel Nof, Or Weinstein
EUROCRYPT (2)4
2017 Optimized Honest-Majority MPC for Malicious Adversaries - Breaking the 1 Billion-Gate Per Second Barrier
abstract
Secure multiparty computation enables a set of parties to securely carry out a joint computation of their private inputs without revealing anything but the output. In the past few years, the efficiency of secure computation protocols has increased in leaps and bounds. However, when considering the case of security in the presence of malicious adversaries (who may arbitrarily deviate from the protocol specification), we are still very far from achieving high efficiency. In this paper, we consider the specific case of three parties and an honest majority. We provide general techniques for improving efficiency of cut-and-choose protocols on multiplication triples and utilize them to significantly improve the recently published protocol of Furukawa et al. (ePrint 2016/944). We reduce the bandwidth of their protocol down from 10 bits per AND gate to 7 bits per AND gate, and show how to improve some computationally expensive parts of their protocol. Most notably, we design cache-efficient shuffling techniques for implementing cut-and-choose without randomly permuting large arrays (which is very slow due to continual cache misses). We provide a combinatorial analysis of our techniques, bounding the cheating probability of the adversary. Our implementation achieves a rate of approximately 1.15 billion AND gates per second on a cluster of three 20-core machines with a 10Gbps network. Thus, we can securely compute 212,000 AES encryptions per second (which is hundreds of times faster than previous work for this setting). Our results demonstrate that high-throughput secure computation for malicious adversaries is possible.
Toshinori Araki, Assi Barak, Jun Furukawa 0001, Tamar Lichter, Yehuda Lindell, Ariel Nof, Kazuma Ohara, Adi Watzman, Or Weinstein
IEEE Symposium on Security and Privacy9