Author ORCID Identifier
Perez - https://orcid.org/0000-0002-2852-2041
Zeadally - https://orcid.org/0000-0002-5982-8190
Document Type
Article
Publication Date
4-30-2018
Publication Title
ACM SIGAPP Applied Computing Review
Volume
18
Issue
1
First Page
7
Last Page
18
Abstract
By using consumer devices such as cellphones, wearables and Internet of Things devices owned by citizens, crowdsensing systems are providing solutions to the community in areas such as transportation, security, entertainment and the environment through the collection of various types of sensor data. Privacy is a major issue in these systems because the data collected can potentially reveal aspects considered private by the contributors of data. We propose the Privacy-Enabled ARchitecture (PEAR), a layered architecture aimed at protecting privacy in privacy-aware crowdsensing systems. We identify and describe the layers of the architecture. We propose and evaluate the design of MetroTrack, a crowdsensing system that is based on the proposed PEAR architecture.
Recommended Citation
Alfredo J. Perez and Sherali Zeadally. 2018. Design and evaluation of a privacy architecture for crowdsensing applications. SIGAPP Appl. Comput. Rev. 18, 1 (March 2018), 7–18. https://doi.org/10.1145/3212069.3212070
Comments
© {Authors | ACM} {2018}. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in {Source Publication}, https://doi.org/10.1145/3212069.3212070}.