2020
DOI: 10.1109/jiot.2020.2967734
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A Hybrid Deep Learning Architecture for Privacy-Preserving Mobile Analytics

Abstract: Internet of Things (IoT) devices and applications are being deployed in our homes and workplaces and in our daily lives. These devices often rely on continuous data collection and machine learning models for analytics and actuations. However, this approach introduces a number of privacy and efficiency challenges, as the service operator can perform arbitrary inferences on the available data. Recently, advances in edge processing have paved the way for more efficient, and private, data processing at the source … Show more

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Cited by 146 publications
(90 citation statements)
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“…With this feature, Transfer Learning is employed in many pieces of research and inspires the design of some frameworks. Osia et al [60], which we have mentioned on Sec. IV-C4 , use Transfer Learning to determine the degree of generality and particularity of a private feature.…”
Section: Enabling Technologiesmentioning
confidence: 71%
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“…With this feature, Transfer Learning is employed in many pieces of research and inspires the design of some frameworks. Osia et al [60], which we have mentioned on Sec. IV-C4 , use Transfer Learning to determine the degree of generality and particularity of a private feature.…”
Section: Enabling Technologiesmentioning
confidence: 71%
“…In simulating human intelligence, AI systems typically demonstrate at least some of the following behaviors associated with human intelligence: planning, learning, reasoning, problem-solving, knowledge representation, perception, motion, and manipulation and, to a lesser extent, social intelligence and creativity. During the past 60 year's development, AI has experienced rise, fall and again rise and fall. The latest rise of AI after 2010's was partially due to the breakthroughs made by deep learning, a method that has achieved human-level accuracy in some interesting areas.…”
Section: A Artificial Intelligencementioning
confidence: 99%
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“…This is particularly true if the data are stored and processed in the cloud. A hybrid deep learning architecture is recently proposed for privacypreserving mobile analytics [26].…”
Section: Privacy In Mobile Deep Learningmentioning
confidence: 99%