Privacyenhancing Cloud Computing Solution for Big Data variety of users cyber data are daily collected by enterprises and governments. These data are processed in order to improve users lifestyle, e.g. improving healthcare and optimizing traffic. Cloud computing is often the only possible strategy which allows processing these big amount of information due to the associated costs. However, data owners remain reluctant to outsource their data to a cloud which may read, use or even sell these data leading on user privacy leakage. These threats have been already observed by EU organization and reflected in many regulations and strategies.This paper present data splitting techniques as one of the most promising technology for privacypreserving computation in a cloud. At first, we propose a new protocol for secure scalar product resistant against honestbutcurious colluding cloud. Then, we compared our new proposal with two most efficient stateoftheart schemes. These schemes are not secure in a colluding security model. While using higher security level of our proposal, we achieved comparable performance. The protocols were implemented in real environment based on Amazon Web Services and, then, an FPGA processor cards implementation is considered in order to speed up the computations.

New group user based privacy preserving cloud auditing protocol Abstract   Cloud storage is now a very popular service for many enterprises and their users. However, ensuring the integrity of the outsourced data is a very challenging problem. The concept of provable data possession is very effective for solving this problem. Based on this concept, in this paper we propose a new groupuserbased privacypreserving secure cloud auditing protocol for enterprise users and analyse its security. This protocol is also constructed on a recently proposed lightweight and privacypreserving secure cloud auditing scheme for group users via a thirdparty medium. We point out that scheme is not secure and that the authenticators corresponding to the outsourced data blocks can be easily forged, that means the cloud servers can delete all the outsourced data but can still give correct proof for the possession of outsourced data, while our protocol has no such shortcoming. The performance analysis results demonstrate that our proposal is very practical and can have largescale applications.