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Differential privacy has emerged as the main definition for private data analysis and machine learning.
Sorting networks and their applications
Kenneth E. Batcher · 1968
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An O ( n log n ) O(n\log n) sorting network
Miklós Ajtai, János Komlós, and Endre Szemerédi · 1983
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Probabilistic counting algorithms for data base applications
Philippe Flajolet and G. Nigel Martin · 1985
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Improved Sorting Networks with O ( log N ) O(\log N) Depth
Mike Paterson · 1990
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Software protection and simulation on oblivious RAMs
Oded Goldreich and Rafail Ostrovsky · 1996
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Timing attacks on implementations of Diffe-Hellman, RSA, DSS, and other systems
Paul C. Kocher · 1996
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Theoretical use of cache memory as a cryptanalytic side-channel
Dan Page · 2002
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Data streams: algorithms and applications
S. Muthukrishnan · 2003
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Cache-timing attacks on AES
Daniel J. Bernstein · 2005
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An improved data stream summary: The count-min sketch and its applications
Graham Cormode and S. Muthukrishnan · 2005
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Cache missing for fun and profit
Colin Percival · 2005
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Calibrating noise to sensitivity in private data analysis
Cynthia Dwork, Frank McSherry, Kobbi Nissim, and Adam Smith · 2006
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Cache attacks and countermeasures: the case of AES
Dag Arne Osvik, Adi Shamir, and Eran Tromer · 2006
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Building castles out of mud: practical access pattern privacy and correctness on untrusted storage
Peter Williams, Radu Sion, and Bogdan Carbunar · 2008
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On the complexity of differentially private data release: Efficient algorithms and hardness results
Cynthia Dwork, Moni Naor, Omer Reingold, Guy N. Rothblum, and Salil Vadhan · 2009
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Hey, you, get off of my cloud: Exploring information leakage in third-party compute clouds
Thomas Ristenpart, Eran Tromer, Hovav Shacham, and Stefan Savage · 2009
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An optimal algorithm for the distinct elements problem
Daniel M. Kane, Jelani Nelson, and David P. Woodruff · 2010
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Oblivious RAM revisited
Benny Pinkas and Tzachy Reinman · 2010
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Data-oblivious external-memory algorithms for the compaction, selection, and sorting of outsourced data
Michael T. Goodrich · 2011
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Privacy-preserving access of outsourced data via oblivious RAM simulation
Michael T. Goodrich and Michael Mitzenmacher · 2011
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Privacy-preserving group data access via stateless oblivious RAM simulation
Michael T. Goodrich, Michael Mitzenmacher, Olga Ohrimenko, and Roberto Tamassia · 2012
Cited alongside, same era.
On the (in)security of hash-based oblivious RAM and a new balancing scheme
Eyal Kushilevitz, Steve Lu, and Rafail Ostrovsky · 2012
Cited alongside, same era.
On significance of the least significant bits for differential privacy
Ilya Mironov · 2012
Cited alongside, same era.
Towards practical oblivious RAM
Emil Stefanov, Elaine Shi, and Dawn Xiaodong Song · 2012
Cited alongside, same era.
Innovative technology for CPU based attestation and sealing
Ittai Anati, Shay Gueron, Simon Johnson, and Vincent Scarlata · 2013
Cited alongside, same era.
Using innovative instructions to create trustworthy software solutions
Matthew Hoekstra, Reshma Lal, Pradeep Pappachan, Carlos Rozas, Vinay Phegade, and Juan del Cuvillo · 2013
Software grand exposure: SGX cache attacks are practical
Ferdinand Brasser, Urs Müller, Alexandra Dmitrienko, Kari Kostiainen, Srdjan Capkun, and Ahmad-Reza Sadeghi · 2017
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Learning with privacy at scale, 2017
Apple Differential Privacy Team · 2017
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Collecting telemetry data privately
Bolin Ding, Janardhan Kulkarni, and Sergey Yekhanin · 2017
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Cache attacks on Intel SGX
Johannes Götzfried, Moritz Eckert, Sebastian Schinzel, and Tilo Müller · 2017
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Cachezoom: How SGX amplifies the power of cache attacks
Ahmad Moghimi, Gorka Irazoqui, and Thomas Eisenbarth · 2017
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Malware Guard Extension: Using SGX to conceal cache attacks
Michael Schwarz, Samuel Weiser, Daniel Gruss, Clementine Maurice, and Stefan Mangard · 2017
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Cited alongside, same era.
Path ORAM: an extremely simple oblivious RAM protocol
Emil Stefanov, Marten van Dijk, Elaine Shi, Christopher W. Fletcher, Ling Ren, Xiangyao Yu, and Srinivas Devadas · 2013
Cited alongside, same era.
The algorithmic foundations of differential privacy
Cynthia Dwork and Aaron Roth · 2014
Cited alongside, same era.
RAPPOR: randomized aggregatable privacy-preserving ordinal response
Úlfar Erlingsson, Vasyl Pihur, and Aleksandra Korolova · 2014
Cited alongside, same era.
The Melbourne shuffle: Improving oblivious storage in the cloud
Olga Ohrimenko, Michael T. Goodrich, Roberto Tamassia, and Eli Upfal · 2014
Cited alongside, same era.
Local, private, efficient protocols for succinct histograms
Raef Bassily and Adam D. Smith · 2015
Cited alongside, same era.
Local, private, efficient protocols for succinct histograms
Raef Bassily and Adam D. Smith · 2015
Cited alongside, same era.
Membership inference attacks against machine learning models
Reza Shokri, Marco Stronati, Congzheng Song, and Vitaly Shmatikov · 2017
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Opaque: An oblivious and encrypted distributed analytics platform
Wenting Zheng, Ankur Dave, Jethro G. Beekman, Raluca Ada Popa, Joseph E. Gonzalez, and Ion Stoica · 2017
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Optorama: Optimal oblivious ram
Gilad Asharov, Ilan Komargodski, Wei-Kai Lin, Kartik Nayak, Enoch Peserico, and Elaine Shi · 2018
Closest in time.
Towards practical differential privacy for SQL queries
Noah Johnson, Joseph P. Near, and Dawn Song · 2018
Closest in time.
Secure computation with differentially private access patterns
Sahar Mazloom and S. Dov Gordon · 2018
Closest in time.
Cacheshuffle: A family of oblivious shuffles
Sarvar Patel, Giuseppe Persiano, and Kevin Yeo · 2018
Closest in time.
Differentially private oblivious RAM
Sameer Wagh, Paul Cuff, and Prateek Mittal · 2018
Closest in time.
The privacy blanket of the shuffle model
Borja Balle, James Bell, Adrià Gascón, and Kobbi Nissim · 2019
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The Secret Sharer: Evaluating and Testing Unintended Memorization in Neural Networks
Nicholas Carlini, Chang Liu, Úlfar Erlingsson, Jernej Kos, and Dawn Song · 2019
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Foundations of differentially oblivious algorithms
T-H. Hubert Chan, Kai-Min Chung, Bruce M. Maggs, and Elaine Shi · 2019
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Distributed differential privacy via shuffling
Albert Cheu, Adam Smith, Jonathan Ullman, David Zeber, and Maxim Zhilyaev · 2019
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Amplification by shuffling: From local to central differential privacy via anonymity
Úlfar Erlingsson, Vitaly Feldman, Ilya Mironov, Ananth Raghunathan, Kunal Talwar, and Abhradeep Thakurta · 2019
Closest in time.
Oblivious sampling algorithms for private data analysis
Sajin Sasy and Olga Ohrimenko · 2019
Closest in time.