Cloud computing is a service by re-arranging resources in the Internet. Cloud service is popular for data storage. The data holder’s privacy is the data stored in cloud and in the encrypted form. The cloud data deduplication is new challenges by the encrypted data, which is for processing in cloud and big data storage. The deduplication is not working on encrypted data. Data has wide applications in zones like keeping money, investigative exploration, prescription and government offices. Order is one of the ordinarily utilized assignments as a part of information mining applications. For back as decade, due to the ascent of different protection issues. The numerous hypothetical and commonsense answers for the order issue have been proposed under diverse security models. The late fame of distributed computing with notwithstanding, clients now has the chance to outsource their information, the information mining assignments and in encoded structure to the cloud. The information on the cloud is in existing security protecting characterization methods and encoded structures are not appropriate. In this paper, the characterization issue over encoded information in system concentrates on fathoming. System proposes a safe k-NN classifier over scrambled information in the cloud. The index is created with the help of Vector base cosine similarity (VCS) multiple strings matching algorithm which matches the pre-defined set of keywords with information in the data files to index them and store relevant data. The classification of information, the information access designs and convention ensures security of client's data inquiry is proposed in this system. To the best of their learning, there work is the first to add to a safe k-NN classifier over scrambled information under the semi-legitimate model.

Cloud Computing Access Control Big Data Data Deduplication Encryption data k-NN classifier Security outsourced databases.