| Title | Tracking location privacy leakage of mobile ad networks at scale |
| Publication Type | Conference Paper |
| Year of Publication | 2018 |
| Authors | Hu, Boyang, Yan, Qiben, Zheng, Yao |
| Conference Name | IEEE INFOCOM 2018 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) |
| Keywords | Adaptation models, adaptive location obfuscation mechanism, advertising, advertising data processing, data privacy, Ecosystems, extensive threat measurements, Google, large-scale measurement study, location data, location-based mobile advertising services, massive data collection, Metrics, mobile ad businesses privacy leakage behaviors, mobile ad ecosystem, mobile ad networks, mobile ads, mobile computing, online advertising ecosystem, potential privacy leakage, privacy, privacy leakage threats, privacy models and measurement, pubcrawl, security of data, targeted ad deliveries |
| Abstract | The online advertising ecosystem is built upon the massive data collection of ad networks to learn the properties of users for targeted ad deliveries. Existing efforts have investigated the privacy leakage behaviors of mobile ad networks. However, there lacks a large-scale measurement study to evaluate the scale of privacy leakage through mobile ads. In this work, we present a study of the potential privacy leakage in location-based mobile advertising services based on a large-scale measurement. We first introduce a threat model in the mobile ad ecosystem, and then design a measurement system to perform extensive threat measurements and assessments. To counteract the privacy leakage threats, we design and implement an adaptive location obfuscation mechanism, which can be used to obfuscate location data in real-time while minimizing the impact to mobile ad businesses. |
| DOI | 10.1109/INFCOMW.2018.8406986 |
| Citation Key | hu_tracking_2018 |
Tracking location privacy leakage of mobile ad networks at scale