By Topic

A Secure Clustering Algorithm for Distributed Data Streams

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)

We present a distributed privacy-preserving protocol for the clustering of data streams. The participants of the se- cure protocol learn cluster centers only on completion of the protocol. Our protocol does not reveal intermediate candidate cluster centers. It is also efficient in terms of communication. The protocol is based on a new memory- efficient clustering algorithm for data streams. Our experi- ments show that, on average, the accuracy of this algorithm is better than that of the well known k-means algorithm, and compares well with BIRCH, but has far smaller mem- ory requirements.

Published in:

Data Mining Workshops, 2007. ICDM Workshops 2007. Seventh IEEE International Conference on

Date of Conference:

28-31 Oct. 2007