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KDD
2002
ACM
157views Data Mining» more  KDD 2002»
14 years 10 months ago
Transforming data to satisfy privacy constraints
Data on individuals and entities are being collected widely. These data can contain information that explicitly identifies the individual (e.g., social security number). Data can ...
Vijay S. Iyengar
ACSW
2007
13 years 11 months ago
Controlling Inference: Avoiding P-level Reduction during Analysis
This paper presents a concept hierarchy-based approach to privacy preserving data collection for data mining called the P-level model. The P-level model allows data providers to d...
Adepele Williams, Ken Barker
TDSC
2011
13 years 5 months ago
CASTLE: Continuously Anonymizing Data Streams
— Most of existing privacy preserving techniques, such as k-anonymity methods, are designed for static data sets. As such, they cannot be applied to streaming data which are cont...
Jianneng Cao, Barbara Carminati, Elena Ferrari, Ki...
GLOBECOM
2006
IEEE
14 years 4 months ago
Requirements and Challenges in the Design of Privacy-aware Sensor Networks
Abstract— Sensor networks are set to become a truly ubiquitous technology that will affect the lives of the people in their application environment. While providing the opportuni...
Efthimia Aivaloglou, Stefanos Gritzalis, Charalabo...
BMCBI
2004
96views more  BMCBI 2004»
13 years 10 months ago
A hybrid clustering approach to recognition of protein families in 114 microbial genomes
Background: Grouping proteins into sequence-based clusters is a fundamental step in many bioinformatic analyses (e.g., homology-based prediction of structure or function). Standar...
Timothy J. Harlow, J. Peter Gogarten, Mark A. Raga...