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

Luceri, L., Cardoso, F.A., Papandrea, M., Giordano, S., Buwaya, J., Kundig, S., Angelopoulos, C.M., Rolim, J., Zhao, Z., Carrera, J., Braun, T., Tossou, A.C.Y., Dimitrakakis, C. and Mitrokotsa, A., 2018. VIVO: a Secure, Privacy-Preserving, and Real-Time Crowd-Sensing Framework for the Internet of Things. Pervasive and mobile computing, 49 (September), pp. 126-138.

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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-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.

Item Type:Article
ISSN:1574-1192
Uncontrolled Keywords:Mobile crowd-sensing; Internet of Things; Big data
Group:Faculty of Science & Technology
ID Code:31245
Deposited By: Unnamed user with email symplectic@symplectic
Deposited On:15 Oct 2018 11:11
Last Modified:15 Oct 2018 11:11

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