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Lightweight Privacy-Preserving Averaging for the Internet of Things
Tristan Allard, Davide Frey, George Giakkoupis, Julien Lepiller

Lightweight Privacy-Preserving Averaging for the Internet of Things

Science & Mathematics Published 2016 Verification Pending

Overview & Synopsis

The number of connected devices is growing continuously , and so is their presence into our everyday lives. From GPS-enabled fitness trackers, to smart fridges that tell us what we need to buy at the grocery store, connected devices—things—have the potential to collect and make available significant amounts of information. On the one hand, this information may provide useful services to users, and constitute a statistical gold mine. On the other, its availability poses serious privacy threats for users. In this paper we propose a novel protocol that makes it possible to aggregate personal information collected by smart devices in the form of an average, while preventing attackers from learning the details of the non-aggregated data.

Indexed from repository: HAL Open Science (hal.science)
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Document Information

Document Title Lightweight Privacy-Preserving Averaging for the Internet of Things
Author / Organization Tristan Allard, Davide Frey, George Giakkoupis, Julien Lepiller
Subject & Discipline Multidisciplinary Academic Open Research
Categories Science & Mathematics
Publication Year 2016
License / Rights Open Access / Creative Commons
Resource Verification Listed PDF (Verification Pending)
Original Host Website HAL Open Science (hal.science)
File Format application/pdf (Portable Document Format)
Language EN
Catalog ID DOC-250866
Original Source Link Visit Source Page on hal.science »