Publication Type
Journal Article
Version
acceptedVersion
Publication Date
3-2018
Abstract
By effectively reaching out to and engaging larger population of mobile users, mobile crowd-sourcing has become a strategy to perform large amount of urban tasks. The recent empirical studies have shown that compared to the pull-based approach, which expects the users to browse through the list of tasks to perform, the push-based approach that actively recommends tasks can greatly improve the overall system performance. As the efficiency of the push-based approach is achieved by incorporating worker's mobility traces, privacy is naturally a concern. In this paper, we propose a novel, 2-stage and user-controlled obfuscation technique that provides a trade off-amenable framework that caters to multi-attribute privacy measures (considering the per-user sensitivity and global uniqueness of locations). We demonstrate the effectiveness of our approach by testing it using the real-world data collected from the well-established TA$Ker platform. More specifically, we show that one can increase its location entropy by 23% with only modest changes to the real trajectories while imposing an additional 24% (< 1 min) of detour overhead on average. Finally, we present insights derived by carefully inspecting various parameters that control the whole obfuscation process.
Keywords
Privacy, Mobile Crowd-sourcing platforms, obfuscation, trajectory, context-aware
Discipline
Computer Sciences | Information Security | Software Engineering
Research Areas
Intelligent Systems and Optimization; Software and Cyber-Physical Systems
Publication
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies
Volume
2
Issue
1
First Page
16:1
Last Page
24
ISSN
2474-9567
Identifier
10.1145/3191748
Publisher
Association for Computing Machinery (ACM)
Citation
KANDAPPU, Thivya; MISRA, Archan; CHENG, Shih-Fen; TANDRIANSYAH, Randy; and LAU, Hoong Chuin.
Obfuscation at-source: Privacy in context-aware mobile crowd-sourcing. (2018). Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies. 2, (1), 16:1-24.
Available at: https://ink.library.smu.edu.sg/sis_research/3976
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1145/3191748