Elliptic Curve Cryptography and Clustering based Privacy Preserving Framework in Cloud Computing
In this technical work, at first, the databases are taken for the Fuzzy C Means (FCM) clustering process to prevent the loss in information and ease of generation of the intermediate database. In the case of FCM clustering, each point comprises of a degree of membership to the clusters, like in the fuzzy logic, rather than being a member of only one cluster. Therefore, the points along the edge of a cluster may exist within the cluster to a lower degree compares to the points present in the cluster centre. For generating the intermediate dataset the l-diversity model algorithm is introduced in order to increase the privacy level. After this, the information for intermediate database to fix up a threshold value is found, depending on the sensitive and non-sensitive data individually. The sensitive data are taken up for the Elliptic Curve Cryptography (ECC) encryption and decryption process. At last, the authorized user can get back the data with querying and the performance of the newly introduced work is compared with the work available in literature.
Author's Name: J. Sasidevi, Dr.R. Sugumar and P. Shanmuga Priya
Volume: Volume 15
Issues: Issue 1
Keywords: Elliptic Curve Cryptography (ECC) Encryption, Fuzzy C Means (FCM) Clustering, l-diversity Model, Cloud Computing and Privacy Preserving Framework