Please use this identifier to cite or link to this item: https://doi.org/10.1109/ICDE.2008.4497561
Title: CASTLE: A delay-constrained scheme for ks-anonymizing data streams
Authors: Cao, J.
Carminati, B.
Ferrari, E.
Tan, K.L. 
Issue Date: 2008
Citation: Cao, J., Carminati, B., Ferrari, E., Tan, K.L. (2008). CASTLE: A delay-constrained scheme for ks-anonymizing data streams. Proceedings - International Conference on Data Engineering : 1376-1378. ScholarBank@NUS Repository. https://doi.org/10.1109/ICDE.2008.4497561
Abstract: 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 continuous, transient and usually unbounded. Moreover, in streaming applications, there is a need to offer strong guarantees on the maximum allowed delay between an incoming data and its anonymized output. To cope with these requirements, in this paper, we present CASTLE (Continuously Anonymizing Streaming data via adaptive cLustEring), a cluster-based scheme that anonymizes data streams on-the-fly and, at the same time, ensures the freshness of the anonymized data by satisfying specified delay constraints. We further show how CASTLE can be easily extended to handle l-diversity [1]. Our extensive performance study shows that CASTLE is efflcient and effective. © 2008 IEEE.
Source Title: Proceedings - International Conference on Data Engineering
URI: http://scholarbank.nus.edu.sg/handle/10635/41568
ISBN: 9781424418374
ISSN: 10844627
DOI: 10.1109/ICDE.2008.4497561
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

20
checked on Oct 16, 2018

WEB OF SCIENCETM
Citations

12
checked on Oct 8, 2018

Page view(s)

61
checked on Oct 6, 2018

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.