Paper Details

— With the advancements in the technology, the amount of data over the internet is getting increased and itbecomes tedious task to handle such a huge amount of data. It is noticed that the clients need to hire the data miningtasks from cloud service providers this is known as outsourcing. Mostly the selection of cloud service provider forvarious services relies upon the choice of clients because the maintenance of confidentiality and privacy is majorconcern nowadays. This study specifically conducted to develop to a novel approach (DSEkNN i.e. Data Split EncryptedkNN) for managing the security by using outsourced kNN (k-Nearest Neighbor) by distributing dataset randomly todifferent CSPs on the basis of their limits for handling data. For the purpose of security two-level or multi levelencryption is applied by using RSA (Rivest-Shammir Adleman) and DNA. In DSEkNN firstly the data is encrypted withRSA and the encrypted data is further crypted with DNA hence it provides two level security to the datasets. For provingthe efficiency of the DSEkNN is compared with OCkNN and PPkNN. After observing the results it is obtained that theproposed work is capable to decrease the burden of data owner’s by reducing the computation time and communicationcost. The simulation is done on two datasets i.e. red wine and white wine.

Mandeep Kaur, Gurbahar Singh, “Security Enhancemnt Based On Hybrid Encryption Approach For Cloud Computing”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 4, Issue 10, pp. 91-96, October 2017.