Secure Two-Party Association Rule Mining Based on One-Pass FP-Tree a one-pass FP-tree method to perform association rule mining without compromising any data privacy among two parties

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Kaosar, Md. Golam and Yi, Xun (2011) Secure Two-Party Association Rule Mining Based on One-Pass FP-Tree a one-pass FP-tree method to perform association rule mining without compromising any data privacy among two parties. International Journal of Information Security and Privacy, 5 (2). pp. 13-32. ISSN 1930-1650 (print) 1930-1669 (online)

Abstract

Data mining, often referred as the major part in knowledge discovery in database (KDD) is the process of discovering knowledge for decision making in business by utilizing patterns or models existed in data. In this paper, it is proposed that a one-pass Frequent Path tree (FP-tree) method will perform association rule mining without compromising the data privacy between two parties.

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Item type	Article
URI	https://vuir.vu.edu.au/id/eprint/9134
DOI	10.4018/jisp.2011040102
Subjects	Historical > FOR Classification > 0806 Information Systems Historical > SEO Classification > 8903 Information Services Historical > Faculty/School/Research Centre/Department > School of Engineering and Science
Keywords	ResPubID23609, Frequent Path tree (FP-tree), Data mining, knowledge discovery in database (KDD), association rule mining, data privacy, security
Citations in Scopus	0 - View on Scopus
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