Visible to the public Right to silence: Establishing map-based Silent Zones for participatory sensing

TitleRight to silence: Establishing map-based Silent Zones for participatory sensing
Publication TypeConference Paper
Year of Publication2014
AuthorsWiesner, K., Feld, S., Dorfmeister, F., Linnhoff-Popien, C.
Conference NameIntelligent Sensors, Sensor Networks and Information Processing (ISSNIP), 2014 IEEE Ninth International Conference on
Date PublishedApril
Keywordsban zones, Buildings, cartography, Cities and towns, data privacy, dynamic map-based blinding out, embedded sensors, habitat density, k-anonymity, large-scale sensing systems, location data, map-based silent zones, Mobile communication, mobile computing, mobile devices, Mobile handsets, mobile phones, participatory sensing, performance evaluation, privacy, privacy level, security of data, Sensors, user privacy protection, Wireless sensor networks

Participatory sensing tries to create cost-effective, large-scale sensing systems by leveraging sensors embedded in mobile devices. One major challenge in these systems is to protect the users' privacy, since users will not contribute data if their privacy is jeopardized. Especially location data needs to be protected if it is likely to reveal information about the users' identities. A common solution is the blinding out approach that creates so-called ban zones in which location data is not published. Thereby, a user's important places, e.g., her home or workplace, can be concealed. However, ban zones of a fixed size are not able to guarantee any particular level of privacy. For instance, a ban zone that is large enough to conceal a user's home in a large city might be too small in a less populated area. For this reason, we propose an approach for dynamic map-based blinding out: The boundaries of our privacy zones, called Silent Zones, are determined in such way that at least k buildings are located within this zone. Thus, our approach adapts to the habitat density and we can guarantee k-anonymity in terms of surrounding buildings. In this paper, we present two new algorithms for creating Silent Zones and evaluate their performance. Our results show that especially in worst case scenarios, i.e., in sparsely populated areas, our approach outperforms standard ban zones and guarantees the specified privacy level.
Citation Key6827657