Security, Privacy and Trust for a Crowd-Sourced Semantic Accessibility Database for Public Transport

Abstract

With the growing popularity of wearable devices and smartphones, mobile crowdsourcing applications (MCNs) have prevailed as a standard for collectively gathering geo-spatial information. This can be very valuable, especially in the public transport section where the associated challenge consists of acquiring area-wide accessibilty information for points of interest. The aim of this work is to describe the implementation of a mobile crowdsourcing platform for the secure recording of accessibility information: mobisaarWORLD. We analyse and discuss which approach is best for its implementation with a focus on ensuring security, privacy and trust. We examine in detail the state-of-the-art in the field, taxonomies of crowdsourcing platforms and the associated security, privacy and trust requirements, issues and countermeasures. In order to measure the effectiveness of the applied countermeasures and the resulting security properties, the platform is then compared to OpenStreetMap. We show that the mobisaarWORLD is able to provide a simple, but effective verification mechanism to ensure data trust and that it can provide personal information privacy, in particular location privacy for its workers.