Obfuscation At-Source

Thivya Kandappu, Archan Misra, Shih-Fen Cheng, Randy Tandriansyah, Hoong Chuin Lau
2018 Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies  
By eectively 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 eciency of the push-based approach is achieved by incorporating
more » ... s mobility traces, privacy is naturally a concern. In this paper, we propose a novel, 2-stage and usercontrolled obfuscation technique that provides a tradeo-amenable framework that caters to multi-attribute privacy measures (considering the per-user sensitivity and global uniqueness of locations). We demonstrate the eectiveness of our approach by testing it using the real-world data collected from the well-established TA$Ker platform. More specically, 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.
doi:10.1145/3191748 fatcat:yzfqwtyrojg43hm2eyy4rogj2i