VIVO: A secure, privacy-preserving, and real-time crowd-sensing framework for the Internet of Things

Authors: Luceri, L., Angelopoulos, C.M. et al.

Journal: Pervasive and Mobile Computing

Volume: 49

Pages: 126-138

ISSN: 1574-1192

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.

http://eprints.bournemouth.ac.uk/31245/

Source: Scopus

VIVO: A secure, privacy-preserving, and real-time crowd-sensing framework for the Internet of Things

Authors: Luceri, L., Angelopoulos, C.M. et al.

Journal: PERVASIVE AND MOBILE COMPUTING

Volume: 49

Pages: 126-138

eISSN: 1873-1589

ISSN: 1574-1192

DOI: 10.1016/j.pmcj.2018.07.003

http://eprints.bournemouth.ac.uk/31245/

Source: Web of Science (Lite)

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

Authors: Angelopoulos, K. et al.

Journal: Pervasive and mobile computing

Publisher: Elsevier

ISSN: 1574-1192

DOI: 10.1016/j.pmcj.2018.07.003

http://eprints.bournemouth.ac.uk/31245/

https://www.sciencedirect.com/science/article/pii/S157411921730648X

Source: Manual

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

Authors: Luceri, L., Angelopoulos, C.M. et al.

Journal: Pervasive and mobile computing

Volume: 49

Issue: September

Pages: 126-138

ISSN: 1574-1192

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.

http://eprints.bournemouth.ac.uk/31245/

Source: BURO EPrints