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

Luceri, Luca; Cardoso, Felipe; Papandrea, Michela; Giordano, Silvia; Buwaya, Julia; Kundig, Stephane; Angelopoulos, Constantinos Marios; Rolim, Jose; Zhao, Zhongliang; Carrera, Jose Luis; Braun, Torsten; Tossou, Aristide Charles Yedia; Dimitrakakis, Christos; Mitrokotsa, Aikaterini (2018). VIVO: a Secure, Privacy-Preserving and Real-Time Crowd-Sensing Framework for the Internet of Things. Pervasive and Mobile Computing, 49, pp. 126-138. Elsevier 10.1016/j.pmcj.2018.07.003

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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.

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