TY  - JOUR
T1  - Fast and Secure Association Rule Mining on Distributed Databases Using FDM and RSA Algorithms
AU - Devi, J. Sumithra AU - Ramakrishnan, M. 
JO  - Journal of Engineering and Applied Sciences
VL  - 13
IS  - 17
SP  - 7187
EP  - 7191
PY  - 2018
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2018.7187.7191
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2018.7187.7191
KW  - Association rule mining
KW  -privacy preservation
KW  -RSA
KW  -data mining security
KW  -distributed data mining
KW  -mining
AB  - In association rule mining, leakage of sensitive data can cause potential threats to privacy and data
protection. In distributed database architecture, performing association rule mining following traditional privacy
preserving techniques are not feasible. We present a novel privacy preserving association rule mining algorithm
that uses cryptosystem technique to maintain privacy. We use FDM technique to find frequent itemsets. The
support count is encrypted using RSA algorithm and forwarded to other sites. We use one data initiator, one
data combiner and other parties as client in ARM process. Experimental results show that this method is flexible
and ensures privacy during global support count calculation process.
ER  -