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.
https://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
https://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
https://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.
https://eprints.bournemouth.ac.uk/31245/
Source: BURO EPrints