PRIVACY PRESERVING POLICY UPDATE FOR BIG DATA ACCESS CONTROL IN THE CLOUD COMPUTING

Big data majorly associated with the high volume and velocity , it is an effective option to store big data in the cloud, as the cloud has capabilities of storing big data and processing high volume of user access requests. Attribute-Based Encryption (ABE) is a promising technique to ensure the end-to-end security of big data in the cloud. However, the policy updating has always been a challenging issue when ABE is used to construct access control schemes. A trivial implementation is to let data owners retrieve the data and re-encrypt it under the new access policy, and then send it back to the cloud. This method, however, incurs a high communication overhead and heavy computation burden on data owners. A novel scheme is proposed that enable efficient access control with dynamic policy updating for big data in the cloud. Developing an outsourced policy updating method for ABE systems is focused. This method can avoid the transmission of encrypted data and minimize the computation work of data owners, by making use of the previously encrypted data with old access policies. Policy updating algorithms is proposed for different types of access policies. An efficient and secure method is proposed that allows data owner to check whether the cloud server has updated the ciphertexts correctly. The analysis shows that this policy updating outsourcing scheme is correct, complete, secure and efficient