Secure System For Data Mining Using Random Decision Tree And Association Rules
In several data processing methodologies because the knowledge becomes a lot of and a lot of to store and handle
in a very single machine. Therefore as an answer to the present, distributed paradigm could be an appropriate situation. By
making use of random decision trees to receive distributed information within the network it becomes simple to handle the
situation. However within the distributed network maintaining privacy of the information becomes a difficult job. Most of
the association rules are getting therefore significant for big datasets. Therefore planned system introduces a thought of
acting horizontal and vertical association victimization Apriori and Éclat rule severally within the distributed paradigm.
Once more privacy is usually an enormous concern within the distributed network that is with success handled by the reverse
circle cipher technique.
Keywords - Random decision tree, Apriori algorithm, Éclat Algorithm, Reverse Circle Cipher Cryptography.