An Efficient Data Security Mechanism Based on Data Groups in Cloud Computing Environment

Abstract

In this paper k-means algorithm has been applied for finding the related group based on the content. In this phase the text and image data will be clustered based on the weight matrix. Then information part (IP) and content part (CP) has been calculated and evaluated. Then advanced encryption standard (AES), data encryption standard (DES) and blowfish algorithm has been applied in the combination or separately based on the threshold and data sensitivity. There is total four sensitivity and threshold levels in our approach. For the lower-level sensitivity AES has been applied. For the middle level sensitivity AES + DES has been applied. For the high-level sensitivity AES + DES + Blowfish algorithm has been applied. In case of image AES + Blowfish has been applied. The results are found to be efficient in terms of generating keys automatically for individual files based on IP and CP. The time taken in the encryption and decryption process in the proposed system is found to be less due to the efficient management of data security and level wise security as per the need. The proposed framework is also efficient in the overall delay and processing due to better security management in comparison to the traditional methods.

Keywords- Data security; Cloud computing; data categorization; K-means.