k-anonymity: a model for protecting privacy
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Algorithm Design
The new Casper: query processing for location services without compromising privacy
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
CarTel: a distributed mobile sensor computing system
Proceedings of the 4th international conference on Embedded networked sensor systems
Exact distributed Voronoi cell computation in sensor networks
Proceedings of the 6th international conference on Information processing in sensor networks
Preventing Location-Based Identity Inference in Anonymous Spatial Queries
IEEE Transactions on Knowledge and Data Engineering
Protecting Location Privacy with Personalized k-Anonymity: Architecture and Algorithms
IEEE Transactions on Mobile Computing
Supporting anonymous location queries in mobile environments with privacygrid
Proceedings of the 17th international conference on World Wide Web
Private queries in location based services: anonymizers are not necessary
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Distributed voronoi diagram computation in wireless sensor networks
Proceedings of the twentieth annual symposium on Parallelism in algorithms and architectures
Nericell: rich monitoring of road and traffic conditions using mobile smartphones
Proceedings of the 6th ACM conference on Embedded network sensor systems
Towards privacy-sensitive participatory sensing
PERCOM '09 Proceedings of the 2009 IEEE International Conference on Pervasive Computing and Communications
Efficient viewpoint assignment for urban texture documentation
Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
A reciprocal framework for spatial K-anonymity
Information Systems
MOBIHIDE: a mobilea peer-to-peer system for anonymous location-based queries
SSTD'07 Proceedings of the 10th international conference on Advances in spatial and temporal databases
Enabling search services on outsourced private spatial data
The VLDB Journal — The International Journal on Very Large Data Bases
Location privacy: going beyond K-anonymity, cloaking and anonymizers
Knowledge and Information Systems
GeoCrowd: enabling query answering with spatial crowdsourcing
Proceedings of the 20th International Conference on Advances in Geographic Information Systems
FAST: differentially private real-time aggregate monitor with filtering and adaptive sampling
Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data
Maximizing the number of worker's self-selected tasks in spatial crowdsourcing
Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
MediaQ: mobile multimedia management system
Proceedings of the 5th ACM Multimedia Systems Conference
| Hi-index | 0.00 |
With the abundance and ubiquity of mobile devices, a new class of applications is emerging, called participatory sensing (PS), where people can contribute data (e.g., images, video) collected by their mobile devices to central data servers. However, privacy concerns are becoming a major impediment in the success of many participatory sensing systems. While several privacy preserving techniques exist in the context of conventional location-based services, they are not directly applicable to the PS systems because of the extra information that the PS systems can collect from their participants. In this paper, we formally define the problem of privacy in PS systems and identify its unique challenges assuming an un-trusted central data server model. We propose PiRi, a privacy-aware framework for PS systems, which enables participation of the users without compromising their privacy. Our extensive experiments verify the efficiency of our approach.