Picture of smart phone in human hand

World leading smartphone and mobile technology research at Strathclyde...

The Strathprints institutional repository is a digital archive of University of Strathclyde's Open Access research outputs. Strathprints provides access to thousands of Open Access research papers by University of Strathclyde researchers, including by Strathclyde researchers from the Department of Computer & Information Sciences involved in researching exciting new applications for mobile and smartphone technology. But the transformative application of mobile technologies is also the focus of research within disciplines as diverse as Electronic & Electrical Engineering, Marketing, Human Resource Management and Biomedical Enginering, among others.

Explore Strathclyde's Open Access research on smartphone technology now...

A fast secure dot product protocol with application to privacy preserving association rule mining

Dong, Changyu and Chen, Liqun (2014) A fast secure dot product protocol with application to privacy preserving association rule mining. In: Advances in Knowledge Discovery and Data Mining. Lecture Notes in Computer Science . Springer, pp. 606-617. ISBN 9783319066073

[img] PDF (Dong-Chen-PAKDD2014-privacy-preserving-association-rule-mining)
Dong_Chen_PAKDD2014_privacy_preserving_association_rule_mining.pdf - Accepted Author Manuscript

Download (302kB)

Abstract

Data mining often causes privacy concerns. To ease the concerns, various privacy preserving data mining techniques have been proposed. However, those techniques are often too computationally intensive to be deployed in practice. Efficiency becomes a major challenge in privacy preserving data mining. In this paper we present an efficient secure dot product protocol and show its application in privacy preserving association rule mining, one of the most widely used data mining techniques. The protocol is orders of magnitude faster than previous protocols because it employs mostly cheap cryptographic operations, e.g. hashing and modular multiplication. The performance has been further improved by parallelization. We implemented the protocol and tested the performance. The test result shows that on moderate commodity hardware, the dot product of two vectors of size 1 million can be computed within 1 minute. As a comparison, the currently most widely used protocol needs about 1 hour and 23 minutes.