The privacy exposure problem in mobile location-based services
Journal
2016 IEEE Global Communications Conference, GLOBECOM 2016 - Proceedings
ISBN
9781509013289
Date Issued
2016-01-01
Author(s)
Abstract
Mobile location-based services (LBSs) empowered by mobile crowdsourcing provide users with context- aware intelligent services based on user locations. As smartphones are capable of collecting and disseminating massive user location-embedded sensing information, privacy preservation for mobile users has become a crucial issue. This paper proposes a metric called privacy exposure to quantify the notion of privacy, which is subjective and qualitative in nature, in order to support mobile LBSs to evaluate the effectiveness of privacy-preserving solutions. This metric incorporates activity coverage and activity uniformity to address two primary privacy threats, namely activity hotspot disclosure and activity transition disclosure. In addition, we propose an algorithm to minimize privacy exposure for mobile LBSs. We evaluate the proposed metric and the privacy-preserving sensing algorithm via extensive simulations. Moreover, we have also implemented the algorithm in an Android-based mobile system and conducted real-world experiments. Both our simulations and experimental results demonstrate that (1) the proposed metric can properly quantify the privacy exposure level of human activities in the spatial domain and (2) the proposed algorithm can effectively cloak users' activity hotspots and transitions at both high and low user-mobility levels.
Subjects
Computer Science - Networking and Internet Architecture; Computer Science - Networking and Internet Architecture; Computer Science - Cryptography and Security
SDGs
Description
This work was supported in part by A*STAR Singapore under SERC grant
1224104046. This work has been partially funded by the European Union's
Horizon 2020 research and innovation programme within the project "Worldwide
Interoperability for SEmantics IoT" under grant agreement Number 723156
1224104046. This work has been partially funded by the European Union's
Horizon 2020 research and innovation programme within the project "Worldwide
Interoperability for SEmantics IoT" under grant agreement Number 723156
Type
conference paper