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  3. VIVO: a Secure, Privacy-Preserving and Real-Time Crowd-Sensing Framework for the Internet of Things

VIVO: a Secure, Privacy-Preserving and Real-Time Crowd-Sensing Framework for the Internet of Things

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DOI
10.7892/boris.109230
Official URL
https://doi.org/10.1016/j.pmcj.2018.07.003
Publisher DOI
10.1016/j.pmcj.2018.07.003
Abstract
Smartphones are a key enabling technology in the Internet of Things (IoT)
for gathering crowd-sensed data. However, collecting crowd-sensing data for re-
search is not simple. Issues related to device heterogeneity, security, and privacy
have prevented the rise of crowd-sensing platforms for scientific data collection.
For this reason, we decided to realize VIVO, an open framework for gathering crowd-sensed Big Data for IoT services, where security and privacy are managed within the framework. VIVO introduces the enrolled crowd-sensing model, which allows the deployment of multiple simultaneous experiments on the mobile phones of volunteers. The collected data can be accessed both at the end of the experiment, as in traditional testbeds, as well as in real-time, as required by many Big Data applications. We present here the VIVO architecture, showing its advantages over existing solutions, and four relevant real-world applications running on top of VIVO.
Date Issued
2018-07
Publication Type
Article
Subject(s)
000 Computer science, knowledge & systems
500 Science > 510 Mathematics
Language(s)
en
Author(s)
Luceri, Luca
Cardoso, Felipe
Papandrea, Michela
Giordano, Silvia
Buwaya, Julia
Kundig, Stephane
Angelopoulos, Constantinos Marios
Rolim, Jose
Zhao, Zhongliang  
Institut für Informatik (INF)  
Carrera, Jose Luis
Braun, Torsten  
Institut für Informatik (INF)  
Tossou, Aristide Charles Yedia
Dimitrakakis, Christos
Mitrokotsa, Aikaterini
Additional Credits
Institut für Informatik (INF)  
Journal
Pervasive and Mobile Computing
Publisher
Elsevier
ISSN
1574-1192
Access(Rights)
restricted
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