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Oblivious Sampling Algorithms for Private Data Analysis
[article]
2020
arXiv
pre-print
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We study secure and privacy-preserving data analysis based on queries executed on samples from a dataset. ...
Experimentally we show that accuracy of models trained with shuffling and sampling is the same for differentially private models for MNIST and CIFAR-10, while sampling provides stronger privacy guarantees ...
Acknowledgements The authors would like to thank anonymous reviewers for useful feedback that helped improve the paper. ...
arXiv:2009.13689v1
fatcat:lw2tgo5yhnbmhekhuwxd5wrosy
SAQE: Practical Privacy-Preserving Approximate Query Processing for Data Federations
2020
Proceedings of the VLDB Endowment
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As a result, private data federations are impractical for common database workloads. ...
A private data federation enables clients to query the union of data from multiple data providers without revealing any extra private information to the client or any other data providers. ...
In our first private sampling algorithm (i.e., an oblivious sampling algorithm), the data providers work together in secure computation to winnow down their input data to a set of samples for use in query ...
dblp:journals/pvldb/BaterP0WR20
fatcat:sfg3d4wkg5h2jfpwfhz272m364
An Algorithmic Framework For Differentially Private Data Analysis on Trusted Processors
[article]
2019
arXiv
pre-print
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Differential privacy has emerged as the main definition for private data analysis and machine learning. ...
The algorithms we design in this framework show interesting interplay of ideas from the streaming algorithms, oblivious algorithms, and differential privacy. ...
PROCHLO [10] , in particular, provides support for differential private data analysis. ...
arXiv:1807.00736v2
fatcat:dyoheafz2vhrvootoagmwa5xyi
Path Oblivious Heap: Optimal and Practical Oblivious Priority Queue
2020
2020 IEEE Symposium on Security and Privacy (SP)
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Our construction also implies a practical and optimal oblivious sorting algorithm which we call Path Oblivious Sort. ...
Finally, we evaluate our algorithm for a multi-party computation scenario and show 7× to 8× reduction in the number of symmetric encryptions relative to the state of the art 1 . ...
for oblivious algorithms. ...
doi:10.1109/sp40000.2020.00037
dblp:conf/sp/Shi20
fatcat:iif2l2dzyrc5zcxjmv6smpxw4i
Resource Oblivious Sorting on Multicores
[chapter]
2010
Lecture Notes in Computer Science
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The parallel complexity (or critical path length) of the algorithm is O(log n log log n), which improves on previous bounds for deterministic sample sort. ...
Using PWS, we obtain a resource oblivious scheduling of our sorting algorithm that matches the performance of the processor-aware version. Our analysis includes the delay incurred by false-sharing. ...
In Section 5, we return to the sorting algorithm, describing the details needed for a resource oblivious implementation, and this is followed by its analysis. ...
doi:10.1007/978-3-642-14165-2_20
fatcat:bkb3otgap5hmlh2kgymmiffcve
Resource Oblivious Sorting on Multicores
2017
ACM Transactions on Parallel Computing
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The parallel complexity (or critical path length) of the algorithm is O( n · n), which improves on previous bounds for optimal cache oblivious sorting. The algorithm also has low false sharing costs. ...
Finally, SPMS is resource oblivious in Athat the dependence on machine parameters appear only in the analysis of its performance, and not within the algorithm itself. ...
In Section 5, we return to the sorting algorithm, describing the details needed for a resource oblivious implementation, and this is followed by its analysis. ...
doi:10.1145/3040221
fatcat:sqh4ozlzq5fq5eommeo6onrscy
MPC meets SNA: A Privacy Preserving Analysis of Distributed Sensitive Social Networks
[article]
2017
arXiv
pre-print
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As a step towards realizing this, we design efficient data-oblivious algorithms for computing the K-shell decomposition and the PageRank centrality measure for a given DSSN. ...
The designed data-oblivious algorithms can be translated into equivalent secure computation protocols. ...
Design and Analysis of Data-Oblivious SNA Algorithms Computing the centrality measure of nodes is a popular network analysis technique for finding important nodes in a network. ...
arXiv:1705.06929v1
fatcat:mqdfhtte7fhd3jmikufoddfe3i
Path Oblivious Heap
[article]
2019
IACR Cryptology ePrint Archive
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Our construction also implies a practical and optimal oblivious sorting algorithm which we call Path Oblivious Sort. ...
More specificially, assuming roughly logarithmic client private storage, Path Oblivious Heap consumes 2× to 7× more bandwidth than the ordinary insecure binary heap; and Path Oblivious Sort consumes 4.5 ...
Acknowledgments The author would like to thank Kai-Min Chung for insightful technical discussions. ...
dblp:journals/iacr/Shi19
fatcat:p3ra5t5jyzbkdlfstl3ajlga2e
KloakDB: A Platform for Analyzing Sensitive Data with K-anonymous Query Processing
[article]
2020
arXiv
pre-print
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A private data federation enables data owners to pool their information for querying without disclosing their secret tuples to one another. ...
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 ...
Private Data Federations A private data federation enables multiple, autonomous database systems to pool their sensitive data for analysis while keeping their input records private. ...
arXiv:1904.00411v2
fatcat:akwbhi7o6vb5zi3sq6rjxvch7q
OLIVE: Oblivious and Differentially Private Federated Learning on Trusted Execution Environment
[article]
2022
arXiv
pre-print
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Thirdly, we propose oblivious yet efficient algorithms to prevent the memory access pattern leakage in OLIVE. ...
Our main technical contributions are the analysis and countermeasures against the vulnerability of TEE in OLIVE. ...
Oblivious algorithms [31, 65, 71] have been proposed to prevent memory access pattern leakage in private information retrieval [45] , private data analysis [4, 61] , and multi-party machine learning ...
arXiv:2202.07165v2
fatcat:a3uveafcqrdhzkulew27luv5hi
Brief announcement
2009
Proceedings of the twenty-first annual symposium on Parallelism in algorithms and architectures - SPAA '09
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In this paper, we describe cache-oblivious sorting algorithms with optimal work, optimal cache complexity and polylogarithmic depth. ...
Cache-oblivious algorithms have the advantage of achieving good sequential cache complexity across all levels of a multi-level cache hierarchy, regardless of the specifics (cache size and cache line size ...
This work was funded in part by IBM, Intel, and the Microsoft-sponsored Center for Computational Thinking. ...
doi:10.1145/1583991.1584024
dblp:conf/spaa/BlellochGS09
fatcat:5dkojwqfvzba7binneyja2itzi
Prochlo
2017
Proceedings of the 26th Symposium on Operating Systems Principles - SOSP '17
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., for application telemetry, error reporting, or demographic profiling. ...
This paper describes a principled systems architecture---Encode, Shuffle, Analyze (ESA)---for performing such monitoring with high utility while also protecting user privacy. ...
We thank the anonymous reviewers for their detailed feedback, and Martín Abadi, Johannes Gehrke, Lea Kissner, Noé Lutz, and Nicolas Papernot for their valuable advice on earlier drafts. ...
doi:10.1145/3132747.3132769
dblp:conf/sosp/BittauEMMRLRKTS17
fatcat:s5icmqnn6jgznjqhh4fo4fzahm
Exploring Differential Obliviousness
2019
International Workshop on Approximation Algorithms for Combinatorial Optimization
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Chan et al. demonstrated that differential obliviousness allows achieving improved efficiency for several algorithmic tasks, including sorting, merging of sorted lists, and range query data structures. ...
In this work, we continue the exploration of differential obliviousness, focusing on algorithms that do not necessarily examine all their input. ...
showed that differential obliviousness does allow achieving improved efficiency for several algorithmic tasks, including sorting (over very small domains), merging of sorted lists, and range query data ...
doi:10.4230/lipics.approx-random.2019.65
dblp:conf/approx/BeimelNZ19
fatcat:krxpfa4ovnhmfce66rni25fo5i
Exploring Differential Obliviousness
[article]
2019
arXiv
pre-print
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Chan et al. demonstrated that differential obliviousness allows achieving improved efficiency for several algorithmic tasks, including sorting, merging of sorted lists, and range query data structures. ...
In this work, we continue the exploration and mapping of differential obliviousness, focusing on algorithms that do not necessarily examine all their input. ...
First note that we only pay for privacy in the executions of algorithm SEARCH (reading and writing to the ORAM is perfectly private). ...
arXiv:1905.01373v2
fatcat:d2n3clr2uncwrhrb7cafxf7zta
Inherit Differential Privacy in Distributed Setting: Multiparty Randomized Function Computation
[article]
2016
arXiv
pre-print
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Importantly, all these protocols satisfy obliviousness and so can be proved to be secure in a simulation based manner. ...
A composition theorem of differentially private protocols is also presented. ...
Much works have been done in differentially private data analysis [32, 33, 34, 25, 35, 36, 37, 38, 39] . Our work tries to extend these algorithms to the distributed setting. ...
arXiv:1604.03001v1
fatcat:jg6piqufj5e2zendmvbqy5oase
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