Privacy-preserving detection of anomalous phenomena in crowdsourced environmental sensing using fine-grained weighted voting.
Mihai MaruseacGabriel GhinitaGoce TrajcevskiPeter ScheuermannPublished in: GeoInformatica (2017)
Keyphrases
- fine grained
- privacy preserving
- weighted voting
- coarse grained
- anomaly detection
- privacy preserving data mining
- vertically partitioned data
- voting method
- access control
- majority voting
- data privacy
- fusion methods
- privacy concerns
- sensitive information
- private information
- privacy protection
- secure multiparty computation
- training set
- hough transform
- data fusion
- support vector machine
- metadata
- search engine
- information retrieval