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A private data federation is a set of autonomous databases that share a unified query interface offering in-situ evaluation of SQL queries over the union of the sensitive data of its members.
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C. Dwork · 2006
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F. D. McSherry · 2009
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A. Narayan and A. Haeberlen · 2012
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Orthogonal Security with Cipherbase
A. Arasu, S. Blanas, K. Eguro, R. Kaushik, D. Kossmann, R. Ramamurthy, and R. Venkatesan · 2013
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PCORI · 2015
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Exchanging de-identified data between hospitals for city-wide health analysis in the Chicago Area HealthLNK data repository (HDR)
PCORI · 2015
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ARMageddon : Cache Attacks on Mobile Devices This paper is included in the Proceedings of the ARMageddon : Cache Attacks on Mobile Devices
M. Lipp, D. Gruss, R. Spreitzer, C. Maurice, S. Mangard, M. Lipp, D. Gruss, R. Spreitzer, and S. Mangard · 2016
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EMP-Toolkit: Efficient Multiparty Computation Toolkit
X. Wang, A. J. Malozemoff, and J. Katz · 2016
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Scaling ORAM for Secure Computation
J. Doerner and A. Shelat · 2017
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Privacy-preserving matrix factorization
V. Nikolaenko, S. Ioannidis, U. Weinsberg, M. Joye, N. Taft, and D. Boneh · 2013
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Oblivious Query Processing
A. Arasu and R. Kaushik · 2014
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Privacy-preserving statistical data analysis on federated databases
D. Bogdanov, L. Kamm, S. Laur, P. Pruulmann-Vengerfeldt, R. Talviste, and J. Willemson · 2014
Cited alongside, same era.
The algorithmic foundations of differential privacy
C. Dwork and A. Roth · 2014
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Rappor: Randomized aggregatable privacy-preserving ordinal response
Ú. Erlingsson, V. Pihur, and A. Korolova · 2014
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Automating Efficient RAM-Model Secure Computation
C. Liu, Y. Huang, E. Shi, J. Katz, and M. Hicks · 2014
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A. Ferraiuolo, R. Xu, D. Zhang, A. C. Myers, and G. E. Suh · 2017
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Composing Differential Privacy and Secure Computation: A case study on scaling private record linkage
X. He, A. Machanavajjhala, C. Flynn, and D. Srivastava · 2017
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The Complexity of Differential Privacy
S. Vadhan · 2017
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Faster secure two-party computation in the single-execution setting
X. Wang, A. J. Malozemoff, and J. Katz · 2017
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The tao of inference in privacy-protected databases
V. Bindschaedler, P. Grubbs, D. Cash, T. Ristenpart, and V. Shmatikov · 2018
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SgxPectre Attacks: Leaking Enclave Secrets via Speculative Execution
G. Chen, S. Chen, Y. Xiao, Y. Zhang, Z. Lin, and T. H. Lai · 2018
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Towards practical differential privacy for sql queries
N. Johnson, J. P. Near, and D. Song · 2018
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Spectre Attacks: Exploiting Speculative Execution
P. Kocher, D. Genkin, D. Gruss, W. Haas, M. Hamburg, M. Lipp, S. Mangard, T. Prescher, M. Schwarz, and Y. Yarom · 2018
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Optimizing error of high-dimensional statistical queries under differential privacy
R. McKenna, G. Miklau, M. Hay, and A. Machanavajjhala · 2018
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Foreshadow: Extracting the Keys to the Intel SGX Kingdom with Transient Out-of-Order Execution
J. Van Bulck, M. Minkin, O. Weisse, D. Genkin, B. Kasikci, F. Piessens, M. Silberstein, T. F. Wenisch, Y. Yarom, R. Strackx, and K. Leuven · 2018
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Conclave Workflow Manager for MPC, 2018
N. Volgushev, M. Schwarzkopf, B. Getchell, A. Lapets, M. Varia, and A. Bestavros · 2018
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Using Differential Privacy to Efficiently Mitigate Side Channels in Distributed Analytics
M. Xu, A. Papadimitriou, A. Feldman, and A. Haeberlen · 2018
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