@article{MAKHILLJEAS2018131716743,
    title = {Fast and Secure Association Rule Mining on Distributed Databases Using FDM and RSA Algorithms},
    journal = {Journal of Engineering and Applied Sciences},
    volume = {13},
    number = {17},
    pages = {7187-7191},
    year = {2018},
    issn = {1816-949x},
    doi = {jeasci.2018.7187.7191},
    url = {https://makhillpublications.co/view-article.php?issn=1816-949x&doi=jeasci.2018.7187.7191},
    author = {J. Sumithra and},
    keywords = {Association rule mining,privacy preservation,RSA,data mining security,distributed data mining,mining},
    abstract = {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.}
    }