Data Mining and Knowledge Discovery
Privacy-preserving regression algorithms
SMO'07 Proceedings of the 7th WSEAS International Conference on Simulation, Modelling and Optimization
A new efficient privacy-preserving scalar product protocol
AusDM '07 Proceedings of the sixth Australasian conference on Data mining and analytics - Volume 70
Privately detecting bursts in streaming, distributed time series data
Data & Knowledge Engineering
ACM Computing Surveys (CSUR)
Information Sciences: an International Journal
Privacy-preserving subgraph discovery
DBSec'12 Proceedings of the 26th Annual IFIP WG 11.3 conference on Data and Applications Security and Privacy
A Privacy Preserving Markov Model for Sequence Classification
Proceedings of the International Conference on Bioinformatics, Computational Biology and Biomedical Informatics
Hi-index | 0.00 |
Outlier detection can lead to the discovery of truly unexpected knowledge in many areas such as electronic commerce, credit card fraud and especially national security. We look at the problem of finding outliers in large distributed databases where privacy/security concerns restrict the sharing of data. Both homogeneous and heterogeneous distribution of data is considered. We propose techniques to detect outliers in such scenarios while giving formal guarantees on the amount of information disclosed.