VIVO: A secure, privacy-preserving, and real-time crowd-sensing framework for the Internet of Things
Author(s)
Luca Luceri
Felipe Cardoso
Michela Papandrea
Silvia Giordano
Julia Buwaya
Stéphane Kundig
Constantinos Marios Angelopoulos
José Rolim
Zhongliang Zhao
Jose Luis Carrera
Torsten Braun
Aristide C.Y. Tossou
Aikaterini Mitrokotsa
Date issued
2018
In
Pervasive and Mobile Computing
Vol
49
From page
126
To page
138
Subjects
Mobile crowd-sensing Internet of Things Big data
Abstract
Smartphones are a key enabling technology in the Internet of Things (IoT) for gathering crowd-sensed data. However, collecting crowd-sensed data for research 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 implemented 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, highlighting its advantages over existing solutions, and four relevant real-world applications running on top of VIVO.
Publication type
journal article
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