PRIVACY PRESERVING ASSOCIATION RULE MINING FROM HIGHLY SECURED OUTSOURCED DATABASES

Database outsourcing is becoming more commercial in the recent distributed and parallel systems. This paper considers Association Rule Mining, Frequent Itemset Mining and Privacy Preserving Mining. There is always a controversy between security and the flexibility. For better mining approaches flexibility is more needed from the Database servers but it increases its security risks on distributed network. In current trend of system setup on distributed clouds the Database servers are separated from the service providing web servers. It also extends the resource of the web servers where they can access more than one Database to analyze and retrieve results. At this scenario the web server acts as the intermediate between the Database servers and the client applications. It is responsibility of the web server to preserve privacy of both client and the Database server. This paper concentrates on both client side and Database server side privacy by introducing the algorithms No-Cache Rules Mining on client and Encrypted Database Access on Database server to preserve both client and server privacy. By internally it follows the traditional Association Rule Mining, Frequent Itemset Mining but in different manner.