Big data is a phrase for data collections that are so massive or complicated that typical data processing applications are unsuitable. Accuracy in big data may lead to more confident decision making, and better judgments may result in higher operational efficiency, cost savings and lower risk. Various methods and techniques including Classification, Clustering, Regression, Artificial Intelligence, Neural Networks, Association Rules, Decision Trees, Genetic Algorithm, and Nearest Neighbor approach are used for data mining from massive data. Cluster is a group of items that belongs to the same class. In other words, related things are grouped in one cluster while dissimilar ones are clustered in another cluster. As a way of protecting digital information, encryption uses one or more mathematical procedures, as well as a "key" or password that can decode the data. Encryption is the process of translating data into a form that cannot be deciphered. Clustering tech-niques may be classed into Partitioning Method, Hierarchical Method, Density- based Method, Grid-Based Method, Model-Based Method, and constraint-based Method. The fundamental purpose of study is to better the security of such clustered huge data during data mining via the cloud. Research study has covered huge data clustering together with clustering mechanism. There have been numerous security hazard to such data. Research effort is centered on the security mechanism for huge data at the time of Data mining in cloud environment.

Encryption, Big Data, Data Mining, Clustering, Security