Preserving Data Confidentiality in Association Rule Mining Using Data Share Allocator Algorithm

These days, investigations of information are becoming essential for various associations all over the globe. By and large, different need to perform examinations on their joined data sets. Privacy security have become a relentless concern wherein business experts do not desire contribute classified transaction data. Therefore, there is requirement build proficient methodology that can process broad mixture convert those into meaningful knowledge user without forfeiting privacy individuals crude information. We devised two unique protocols frequent mining itemsets in horizontally partitioned datasets while maintaining privacy. In such scenario, possessors outwork tasks multiparty by preserving The proposed framework model encompasses or more who encrypt dispense encrypted clouds share allocator algorithm. This protects possessor raw from other clouds. To guarantee privacy, we plan enhanced homomorphic encryption conspire. Our approach ensures during communication accumulation guarantees no adversity incidental consequences utility.