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Applying Secure Multi-Party Computation In Practice

Riivo Talviste
2017 Zenodo  
In this work, we present solutions for technical difficulties in deploying secure multi-party computation in real-world applications.  ...  The main contribution of this work is an end-to-end process description of deploying secure multi-party computation for the first large-scale registry-based statistical study on linked databases.  ...  .: A Practical Analysis of Oblivious Sorting Algorithms for Secure Multi-party Computation. In: Proceedings of the 19th Nordic Conference on Secure IT Systems.  ... 
doi:10.5281/zenodo.1116316 fatcat:jhzsyrgt2beptj6jdb6axtvzfy

Secure Stable Matching at Scale

Jack Doerner, David Evans, abhi shelat
2016 Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security - CCS'16  
However, stable matching algorithms have previously been considered infeasible for execution in a secure multi-party context on non-trivial inputs because they are computationally intensive and involve  ...  Secure multi-party computation offers the possibility of private matching processes that do not rely on any common trusted third party.  ...  Acknowledgments The authors thank Samee Zahur for insightful conversations about this work and assistance with Obliv-C and ORAM, and Elaine Shi for constructive comments and advice.  ... 
doi:10.1145/2976749.2978373 dblp:conf/ccs/DoernerES16 fatcat:4wgv35kgwrhg5ob6ognyarchf4

GraphSC: Parallel Secure Computation Made Easy

Kartik Nayak, Xiao Shaun Wang, Stratis Ioannidis, Udi Weinsberg, Nina Taft, Elaine Shi
2015 2015 IEEE Symposium on Security and Privacy  
We build GraphSC and demonstrate, using several algorithms as examples, that secure computation can be brought into the realm of practicality for big data analysis.  ...  Importantly, our secure version of graph-based algorithms incurs a small logarithmic overhead in comparison with the non-secure parallel version.  ...  By creating such a framework, we can bring secure computation to the practical realm for modern massive datasets.  ... 
doi:10.1109/sp.2015.30 dblp:conf/sp/NayakWIWTS15 fatcat:ifmmdvlrd5c7nj5otbbckdne6m

Privacy Preserving Joins

Yaping Li, Minghua Chen
2008 2008 IEEE 24th International Conference on Data Engineering  
We evaluate the performance of our algorithms by numerical examples and show the performance superiority of our approach over that of the secure multi-party computation.  ...  Based on this new definition, we propose three provable correct and secure algorithms to compute general joins of arbitrary predicates.  ...  Another approach is along the lines of secure multi-party computation problem where parties collectively perform a computation over their data [11] .  ... 
doi:10.1109/icde.2008.4497553 dblp:conf/icde/LiC08 fatcat:fmkylcgikneqbje6dz7jvq25fi

From Oblivious AES to Efficient and Secure Database Join in the Multiparty Setting [chapter]

Sven Laur, Riivo Talviste, Jan Willemson
2013 Lecture Notes in Computer Science  
For most share-computing systems, even a coalition of parties cannot learn anything about private data unless the size of a coalition is over a threshold.  ...  Development and implementation of such multi-party computing platforms is an active research area.  ...  Also, we would like to thank Helger Lipmaa for insightful theoretical suggestions.  ... 
doi:10.1007/978-3-642-38980-1_6 fatcat:sih2pvrdybarzgv3kbs2guyxg4

Privacy-Preserving Statistical Data Analysis on Federated Databases [chapter]

Dan Bogdanov, Liina Kamm, Sven Laur, Pille Pruulmann-Vengerfeldt, Riivo Talviste, Jan Willemson
2014 Lecture Notes in Computer Science  
In this paper, we propose a novel way to combine secure multi-party computation technology with federated database systems to preserve privacy in statistical studies that combine and analyse data from  ...  We describe an implementation on two real-world platforms-the Sharemind secure multi-party computation and the X-Road database federation platform.  ...  for their help in generating the artificial data used in the experiments of this paper.  ... 
doi:10.1007/978-3-319-06749-0_3 fatcat:uvfasioddjfgflnn3px2xw54nu

A secure computation framework for SDNs

Nachikethas A. Jagadeesan, Ranjan Pal, Kaushik Nadikuditi, Yan Huang, Elaine Shi, Minlan Yu
2014 Proceedings of the third workshop on Hot topics in software defined networking - HotSDN '14  
To ensure the data-oblivious property, both parts are realized using an oblivious sorting algorithm, namely, randomized shell sort [1] .  ...  Given recent advances in making SMPC faster [2] , we find it suitable to use multi-party computation to achieve the following security goals in SDNs: (i) When a subset of the controllers are compromised  ... 
doi:10.1145/2620728.2620768 dblp:conf/sigcomm/JagadeesanPNHSY14 fatcat:eltwdsry6fb7dchuf5eg3ayfsa

Distributed Oblivious RAM for Secure Two-Party Computation [chapter]

Steve Lu, Rafail Ostrovsky
2013 Lecture Notes in Computer Science  
As alluded above, our two-server Oblivious RAM protocol leads to a novel application in the realm of secure two-party RAM program computation.  ...  We show that our Oblivious RAM construction can be composed with an extended version of the Ostrovsky-Shoup compiler to obtain a new method for secure two-party program computation with lower overhead  ...  Application to Secure Two-Party RAM Computation In this section, we describe how our multi-party Oblivious RAM simulation can be applied to the setting of secure two-party computation on RAM programs.  ... 
doi:10.1007/978-3-642-36594-2_22 fatcat:xvo5757svfboplireewndmv3ce

Rmind: A Tool for Cryptographically Secure Statistical Analysis

Dan Bogdanov, Liina Kamm, Sven Laur, Ville Sokk
2018 IEEE Transactions on Dependable and Secure Computing  
Secure multi-party computation platforms are becoming more and more practical. This has paved the way for privacy-preserving statistical analysis using secure multi-party computation.  ...  We give descriptions of the privacy-preserving algorithms and benchmark results that show the feasibility of our solution.  ...  One example of a practically feasible PDK is secure multi-party computation on additively secret shared data [9] .  ... 
doi:10.1109/tdsc.2016.2587623 fatcat:7iw65bregfeaxn44eaew4nwhem

Round-Efficient Oblivious Database Manipulation [chapter]

Sven Laur, Jan Willemson, Bingsheng Zhang
2011 Lecture Notes in Computer Science  
Even though the generic methods of secure multi-party computations have been known for decades [36, 7, 15] , practical implementations of the respective frameworks have emerged only recently, e.g.  ...  Most of the multi-party computation frameworks can be viewed as oblivious databases where data is stored and processed in a secret-shared form.  ...  Acknowledgments This research was supported by Estonian Science Foundation grant #8058, the European Regional Development Fund through the Estonian Center of Excellence in Computer Science (EXCS), and  ... 
doi:10.1007/978-3-642-24861-0_18 fatcat:admnnitkqrc3lfeqii7uyg7tsm

A Secure Genetic Algorithm for the Subset Cover Problem and Its Application to Privacy Protection [chapter]

Dan Bogdanov, Keita Emura, Roman Jagomägis, Akira Kanaoka, Shin'ichiro Matsuo, Jan Willemson
2014 Lecture Notes in Computer Science  
As an application of our algorithm, we consider the problem of securely outsourcing risk assessment of an end user computer environment.  ...  We propose a method for applying genetic algorithms to confidential data. Genetic algorithms are a well-known tool for finding approximate solutions to various optimization and searching problems.  ...  This research has been supported by the European Regional Development Fund through the Estonian Center of Excellence in Computer Science (EXCS), UaESMC project financed by the EU 7th Framework Programme  ... 
doi:10.1007/978-3-662-43826-8_8 fatcat:55r4uocvufagtaefb2tyerqume

Practically Efficient Secure Single-Commodity Multi-market Auctions [chapter]

Abdelrahaman Aly, Mathieu Van Vyve
2017 Lecture Notes in Computer Science  
We introduce a novel greedy algorithm and its corresponding privacy preserving implementation using secure multi-party computation.  ...  Furthermore, we provide computational results with a specific C++ implementation of our algorithm and the necessary MPC primitives.  ...  The authors are grateful to Olivier Pereira and Ignacio Aravena for their feedback. The scientific responsibility is assumed by the authors.  ... 
doi:10.1007/978-3-662-54970-4_7 fatcat:2m44kfiwdbcttdmllviyupcsbm

Data-oblivious graph algorithms for secure computation and outsourcing

Marina Blanton, Aaron Steele, Mehrdad Alisagari
2013 Proceedings of the 8th ACM SIGSAC symposium on Information, computer and communications security - ASIA CCS '13  
A data-oblivious algorithm is defined as having the same sequence of operations regardless of the input data and dataindependent memory accesses.  ...  This work treats the problem of designing data-oblivious algorithms for classical and widely used graph problems.  ...  It introduced data-oblivious algorithms for calculating classical geometric problems, such as convex hull and all nearest neighbors, using secure multi-party computation.  ... 
doi:10.1145/2484313.2484341 dblp:conf/ccs/BlantonSA13 fatcat:m7h5crkj2nefhbcw5pbfu2hr5a

KloakDB: A Platform for Analyzing Sensitive Data with K-anonymous Query Processing [article]

Madhav Suresh, Zuohao She, William Wallace, Adel Lahlou, Jennie Rogers
2020 arXiv   pre-print
KloakDB offers a semi-oblivious computing framework, k-anonymous query processing.  ...  Currently private data federations compute their queries fully-obliviously, guaranteeing that no information is revealed about the sensitive inputs of a data owner to their peers by observing the query's  ...  Speaking broadly, there are two common methods for methods for general-purpose computing over the data of two or more mutually distrustful parties: in software with secure multi-party computation [59]  ... 
arXiv:1904.00411v2 fatcat:akwbhi7o6vb5zi3sq6rjxvch7q

Secure Anonymous Broadcast [article]

Mahnush Movahedi and Jared Saia and Mahdi Zamani
2014 arXiv   pre-print
Our main strategy for achieving scalability is to perform local communications (and computations) among a logarithmic number of parties.  ...  Our protocol is provably secure against traffic analysis, does not require any trusted party, and is completely load-balanced.  ...  Multi-party shuffling: All or a subset of parties participate in a multi-party protocol to obliviously generate a random permutation of the sequence of message they hold. 3.  ... 
arXiv:1405.5326v1 fatcat:22npksye7vaqlg72ipshrmc2eu
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