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Large-Scale Secure Computation: Multi-party Computation for (Parallel) RAM Programs
[chapter]
2015
Lecture Notes in Computer Science
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to polylogarithmic factors the computation, parallel time, and memory complexities of the PRAM program, aside from a one-time execution of a broadcast protocol per party. ...
More specifically, we demonstrate load-balanced, statistically secure computation protocols for computing Parallel RAM (PRAM) programs, handling (1/3 − ) fraction malicious players, while preserving up ...
The CPU jobs store the local state and perform the computations of their corresponding CPU. ...
doi:10.1007/978-3-662-48000-7_36
fatcat:bzvrj2j435ahffuaptnyfew32q
PPCA: Privacy-preserving Principal Component Analysis Using Secure Multiparty Computation(MPC)
[article]
2021
arXiv
pre-print
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Using Principal Component Analysis (PCA) as an example, we show that by considering the unique performance characters of the MPC platform, we can design highly effective algorithm-level optimizations, ...
People have built several multi-party-computation (MPC)-based frameworks to provide theoretically guaranteed privacy, the poor performance of real-world algorithms have always been a challenge. ...
The group's target is to collaboratively perform a principal component analysis (PCA) and compute the projection matrix of size × , where 1 ≤ ≤ is an input to the algorithm, such that the -th column of ...
arXiv:2105.07612v1
fatcat:jmh6jsaulfempjxzp6kylms45u
Secure Multi-party Computation for Inter-organizational Process Mining
[chapter]
2020
Lecture Notes in Business Information Processing
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Since a direct implementation of DFG construction in Sharemind suffers from scalability issues, we propose to rely on vectorization of event logs and to employ a divide-andconquer scheme for parallel processing ...
The use of such tools for inter-organizational process analysis is hampered by the fact that such processes involve independent parties who are unwilling to, or sometimes legally prevented from, sharing ...
This research is partly funded by ERDF via the Estonian Centre of Excellence in ICT (EXCITE) and the IT Academy programme. ...
doi:10.1007/978-3-030-49418-6_11
fatcat:uzrgutcm4jhkdbnhtqw2hqcaqe
Secure Multi-Party Computation for Inter-Organizational Process Mining
[article]
2020
arXiv
pre-print
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Since a direct implementation of DFG construction in Sharemind suffers from scalability issues, the paper proposes to rely on vectorization of event logs and to employ a divide-and-conquer scheme for parallel ...
The use of such tools for inter-organizational process analysis is hampered by the fact that such processes involve independent parties who are unwilling to, or sometimes legally prevented from, sharing ...
This research is partly funded by ERDF via the Estonian Centre of Excellence in ICT (EXCITE) and the IT Academy programme. ...
arXiv:1912.01855v2
fatcat:hpah7qem5zbc7mow2ouq4ldhfm
SEPIA: Security through Private Information Aggregation
[article]
2010
arXiv
pre-print
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Optimizing performance of parallel invocations, we implement our protocols along with a complete set of basic operations in a library called SEPIA. ...
This improvement paves the way for new applications of MPC in the area of networking. ...
Also, we want to thank Lisa Barisic and Dominik Schatzmann for their contributions and Vassilis Zikas for assisting with MPC matters. ...
arXiv:0903.4258v4
fatcat:yc5qnzpw3ncilpsjxnbijcoqou
Secret Sharing MPC on FPGAs in the Datacenter
[article]
2020
arXiv
pre-print
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The presence of Field Programmable Gate Array (FPGA) hardware in datacenters can provide accelerated computing as well as low latency, high bandwidth communication that bolsters the performance of MPC ...
We compare our hardware design to the original authors' software implementations of Secret Sharing and to work accelerating MPC protocols based on Garbled Circuits with FPGAs. ...
Selected MPC Protocol Within the category of MPC protocols based on Secret Sharing, we selected a protocol by Araki et al. ...
arXiv:2007.00826v1
fatcat:nsj4n3gh75cepf77o4jxq3flyu
Conclave
2019
Proceedings of the Fourteenth EuroSys Conference 2019 CD-ROM on ZZZ - EuroSys '19
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When parties trust others with specific subsets of the data, Conclave applies new hybrid MPC-cleartext protocols to run additional steps outside of MPC and improve scalability further. ...
Conclave scales to data sets between three and six orders of magnitude larger than state-of-the-art MPC frameworks support on their own. ...
Acknowledgements We thank Ran Canetti, Tore Kasper Frederiksen, Derek Leung, and Nickolai Zeldovich for their helpful feedback on drafts of this paper. ...
doi:10.1145/3302424.3303982
dblp:conf/eurosys/VolgushevSGVLB19
fatcat:xn7ichau3ndr5kfmvdqkp5wfk4
Recent Advances in Practical Secure Multi-Party Computation
2020
IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences
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In this paper, we introduce the basic matters on MPC and show recent practical advances. We first explain the settings, security notions, and cryptographic building blocks of MPC. ...
Secure multi-party computation (MPC) allows a set of parties to compute a function jointly while keeping their inputs private. ...
We do not mention the details in each section, parallelizing the computations and communications are the major premises to improve the performance in SS-based MPC. ...
doi:10.1587/transfun.2019dmi0001
fatcat:zw747hbb2vfpfl3jdpti4tdeum
Privacy-Preserving Multi-Party Directory Services
2019
EAI Endorsed Transactions on Security and Safety
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In the era of big data, the data-processing pipeline becomes increasingly distributed among multiple sites. To connect data consumers with remote producers, a public directory service is essential. ...
A conventional remedy is to identify the private part of the computation (e.g., by data-flow analysis [17, 52] ) and to map only this part to the MPC. ...
The pre-computation framework improves the performance by minimizing the private-data computation and realizing the publicdata only pre-computation in a data-parallel fashion. ...
doi:10.4108/eai.29-7-2019.159627
fatcat:jjznhjlzjzhnhfae7f66a2xkye
Programming Support for an Integrated Multi-Party Computation and MapReduce Infrastructure
2015
2015 Third IEEE Workshop on Hot Topics in Web Systems and Technologies (HotWeb)
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The highlevel programming language provided to the user is accompanied by static analysis algorithms that allow the programmer to reason about the efficiency of the protocol before compiling and running ...
capable of supporting MapReduce [1] operations in combination with multi-party computation (MPC). ...
This work was supported in part by NSF Grants: #1430145, #1414119, #1347522, and #1012798. ...
doi:10.1109/hotweb.2015.21
dblp:conf/hotweb/VolgushevLB15
fatcat:7o57vbl6kjfsvhoiji3o7bv2gu
Secure Multiparty AES
[chapter]
2010
Lecture Notes in Computer Science
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We propose several variants of a secure multiparty computation protocol for AES encryption. ...
We implemented the variants using VIFF, a software framework for implementing secure multiparty computation (MPC). ...
Another improvement is an MPC protocol providing active security which allows preprocessing, i.e., performing some computations without knowing the input to reduce the online time [6] . ...
doi:10.1007/978-3-642-14577-3_31
fatcat:ad6o7rsmrredrm77bsvdv7vv3e
DEMO
2016
Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security - CCS'16
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Musketeer automatically generates code for both the sensitive parts of a workflow, which are executed in MPC, and the remaining portions of the computation, which run on scalable, widely-deployed analytics ...
Secure multi-party computation (MPC) allows multiple parties to perform a joint computation without disclosing their private inputs. ...
Acknowledgements Research supported by NSF awards #1414119 and #1430145. ...
doi:10.1145/2976749.2989034
dblp:conf/ccs/VolgushevSLVB16
fatcat:jiho4j436zam7ll5zysbcw3uom
SafeRegions: Performance Evaluation of Multi-party Protocols on HBase
2016
2016 IEEE 35th Symposium on Reliable Distributed Systems Workshops (SRDSW)
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Building strong data privacy mechanisms on top of common database systems is possible but has a significant impact on the system's resources, computational capabilities and performance. ...
Notably, the amount of useful computation that may be done over strongly encrypted data is close to none, which defeats the purpose of offloading computation to thirdparty services. ...
The research leading to these results has received funding from different sources. Rogério Pontes is financed by the ERDF -European Regional Development ...
doi:10.1109/srdsw.2016.16
dblp:conf/srds/PontesMPV16
fatcat:rzl5vvo3w5hnnhu672irfw7spa
Privacy-preserving GWAS analysis on federated genomic datasets
2015
BMC Medical Informatics and Decision Making
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Our method is to layer the GWAS computations on top of secure multi-party computation (MPC) systems. ...
Federated genomic data analysis holds the promise of enabling cross-institution collaboration for effective GWAS, but it raises concerns about patient privacy and medical information confidentiality (as ...
Declarations Publication funding for this supplement was supported by iDASH U54HL108460, iDASH linked R01HG007078 (Indiana University), NHGRI K99HG008175 and NLM R00LM011392. ...
doi:10.1186/1472-6947-15-s5-s2
pmid:26733045
pmcid:PMC4699163
fatcat:zw34y6iynvf4rgg6qnoolcs2ea
Role-Based Ecosystem for the Design, Development, and Deployment of Secure Multi-Party Data Analytics Applications
2019
2019 IEEE Cybersecurity Development (SecDev)
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Our framework acknowledges and leverages a novel assortment of roles that emerge from the fundamental ways in which MPC protocols support federation of functionalities and responsibilities. ...
This framework can not only guide the development of an ecosystem of modular and composable MPC tools, but can make explicit some of the opportunities that researchers and software engineers (and any organizations ...
ACKNOWLEDGMENT This work is partially supported by the NSF (under Grants #1430145, #1414119, #1718135, and #1739000) and the Honda Research Institutes. ...
doi:10.1109/secdev.2019.00023
dblp:conf/secdev/LapetsAIQVBJ19
fatcat:w3j2yfzuprffvk7qaru2yx6zmq
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