Privacy-preserving associative classification

Abstract

The massive amount of data, if publicly available, can be stored and shared securely for analysis and advancement. Mining of association rule besides classification technique is skilled of discovering useful patterns from big datasets. This technique results in the if-then form of rules and these rules are simple for end users to understand and easy for prediction. But it is apparent that the gathering and analysis of such data causes a serious menace to confidentiality and freedom. Hence, it interprets a field of privacy-preservation of data mining, which deals with efficient conduction and application of data mining without scarifying the privacy of data. This paper puts effort on the construction of class association rules generated by associative classification and applying privacy-preserving techniques on these rules to prevent its disclosure to the uncertified population.