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With the advance of machine learning and the internet of things (IoT), security and privacy have become key concerns in mobile services and networks.
On data banks and privacy homomorphisms
Ronald L Rivest, Len Adleman, Michael L Dertouzos, et al · 1978
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A public key cryptosystem and a signature scheme based on discrete logarithms
Taher ElGamal · 1985
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Ntru: A ring-based public key cryptosystem
Jeffrey Hoffstein, Jill Pipher, and Joseph H Silverman · 1998
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Public-key cryptosystems based on composite degree residuosity classes
Pascal Paillier · 1999
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A generalisation, a simpli. cation and some applications of paillier’s probabilistic public-key system
Ivan Damgård and Mads Jurik · 2001
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Differential privacy
Cynthia Dwork · 2006
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Calibrating noise to sensitivity in private data analysis
Cynthia Dwork, Frank McSherry, Kobbi Nissim, and Adam Smith · 2006
Earlier work this paper cites.
Our data, ourselves: Privacy via distributed noise generation
Cynthia Dwork, Krishnaram Kenthapadi, Frank McSherry, Ilya Mironov, and Moni Naor · 2006
Earlier work this paper cites.
Multi-bit cryptosystems based on lattice problems
Akinori Kawachi, Keisuke Tanaka, and Keita Xagawa · 2007
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A fully homomorphic encryption scheme
Craig Gentry and Dan Boneh · 2009
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On ideal lattices and learning with errors over rings
Vadim Lyubashevsky, Chris Peikert, and Oded Regev · 2010
Earlier work this paper cites.
Homomorphic encryption: From private-key to public-key
Ron Rothblum · 2011
Earlier work this paper cites.
On-the-fly multiparty computation on the cloud via multikey fully homomorphic encryption
Adriana López-Alt, Eran Tromer, and Vinod Vaikuntanathan · 2012
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Fully homomorphic encryption without modulus switching from classical gapsvp
Zvika Brakerski · 2012
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Somewhat practical fully homomorphic encryption
Junfeng Fan and Frederik Vercauteren · 2012
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A tutorial on human activity recognition using body-worn inertial sensors
Andreas Bulling, Ulf Blanke, and Bernt Schiele · 2014
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
Cited alongside, same era.
Multi-identity and multi-key leveled fhe from learning with errors
Michael Clear and Ciaran McGoldrick · 2015
Cited alongside, same era.
Secure multiparty computation
Ronald Cramer, Ivan Bjerre Damgård, et al · 2015
Cited alongside, same era.
Federated learning: Strategies for improving communication efficiency
Jakub Konečnỳ, H Brendan McMahan, Felix X Yu, Peter Richtárik, Ananda Theertha Suresh, and Dave Bacon · 2016
Cited alongside, same era.
Homomorphic aes evaluation using the modified ltv scheme
Yarkın Doröz, Yin Hu, and Berk Sunar · 2016
Cited alongside, same era.
Two round multiparty computation via multi-key fhe
Differentially private federated learning: A client level perspective
Robin C Geyer, Tassilo Klein, and Moin Nabi · 2017
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Multi-key privacy-preserving deep learning in cloud computing
Ping Li, Jin Li, Zhengan Huang, Tong Li, Chong-Zhi Gao, Siu-Ming Yiu, and Kai Chen · 2017
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Machine learning with adversaries: Byzantine tolerant gradient descent
Peva Blanchard, El Mahdi El Mhamdi, Rachid Guerraoui, and Julien Stainer · 2017
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Federated learning with non-iid data, 2018
Yue Zhao, Meng Li, Liangzhen Lai, Naveen Suda, Damon Civin, and Vikas Chandra · 2018
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Byzantine-robust distributed learning: Towards optimal statistical rates
Dong Yin, Yudong Chen, Ramchandran Kannan, and Peter Bartlett · 2018
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Pratyay Mukherjee and Daniel Wichs · 2016
Cited alongside, same era.
Federated learning: Strategies for improving communication efficiency
Jakub Konečnỳ, H Brendan McMahan, Felix X Yu, Peter Richtárik, Ananda Theertha Suresh, and Dave Bacon · 2016
Cited alongside, same era.
Practical secure aggregation for federated learning on user-held data
Keith Bonawitz, Vladimir Ivanov, Ben Kreuter, Antonio Marcedone, H Brendan McMahan, Sarvar Patel, Daniel Ramage, Aaron Segal, and Karn Seth · 2016
Cited alongside, same era.
Deep learning with differential privacy
Martin Abadi, Andy Chu, Ian Goodfellow, H Brendan McMahan, Ilya Mironov, Kunal Talwar, and Li Zhang · 2016
Cited alongside, same era.
Cryptonets: Applying neural networks to encrypted data with high throughput and accuracy
Ran Gilad-Bachrach, Nathan Dowlin, Kim Laine, Kristin Lauter, Michael Naehrig, and John Wernsing · 2016
Cited alongside, same era.
Deep models under the gan: information leakage from collaborative deep learning
Briland Hitaj, Giuseppe Ateniese, and Fernando Perez-Cruz · 2017
Cited alongside, same era.
Privacy-preserving deep learning via additively homomorphic encryption
Yoshinori Aono, Takuya Hayashi, Lihua Wang, Shiho Moriai, et al · 2017
Cited alongside, same era.
Luca Melis, Congzheng Song, Emiliano De Cristofaro, and Vitaly Shmatikov · 2019
Later among the works it cites.
Deep leakage from gradients
Ligeng Zhu, Zhijian Liu, and Song Han · 2019
Later among the works it cites.
Probabilistic encryption & how to play mental poker keeping secret all partial information
Shafi Goldwasser and Silvio Micali · 2019
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Efficient multi-key homomorphic encryption with packed ciphertexts with application to oblivious neural network inference
Hao Chen, Wei Dai, Miran Kim, and Yongsoo Song · 2019
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Verifynet: Secure and verifiable federated learning
Guowen Xu, Hongwei Li, Sen Liu, Kan Yang, and Xiaodong Lin · 2019
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Up-fall detection dataset: A multimodal approach
Lourdes Martinez-Villaseñor, Hiram Ponce, Jorge Brieva, Ernesto Moya-Albor, José Nuñez Martinez, and Carlos Peñafort-Asturiano · 2019
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A privacy-preserving and verifiable federated learning scheme
Xianglong Zhang, Anmin Fu, Huaqun Wang, Chunyi Zhou, and Zhenzhu Chen · 2020
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Privacy-preserving federated learning framework based on chained secure multi-party computing
Yong Li, Yipeng Zhou, Alireza Jolfaei, Dongjin Yu, Gaochao Xu, and Xi Zheng · 2020
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Drynx: Decentralized, secure, verifiable system for statistical queries and machine learning on distributed datasets
David Froelicher, Juan Ramón Troncoso-Pastoriza, Joao Sa Sousa, and Jean-Pierre Hubaux · 2020
Later among the works it cites.
Internet of things (iot) connected devices installed base worldwide from 2015 to 2025(in billions)
Statista · 2025
Closest in time.