Trends and research directions for privacy preserving approaches on the cloud

With advancements in hardware and software capabilities, cloud computing has evolved into a widely utilized paradigm for pay per use and robust computation. An unparalleled repository of user sensitive data that resides on the cloud poses severe threat to the privacy of individuals. Users authenticate, store and perform computations on their data using cloud services. From the cloud's perspective, it gathers additional user data via ubiquitous devices, mines this information to offer personalized services like recommendations and disseminates the results. However, the interactions between the cloud and user at each stage of this pipeline development is limited by privacy concerns. In recent years, much work has been done on designing privacy preserving approaches for improving cloud security and the trust network. A wide array of data mining, cryptography and information hiding techniques have been applied to cater to different aspects of providing risk free work environment in the cloud. Given the lack of management of this information, a systematic investigation is required to structurally organize the topics studied. This paper aims to clearly portray the stringent and urgent need for applying privacy preserving approaches to the cloud and highlight the relevant work that has been done along these lines. The key objective is to identify important areas of user-cloud interaction and demonstrate a survey on the state of the art algorithms that have led to improved cloud privacy in these areas The focus is on exploring criteria for the impact of such approaches on user cloud interaction. An understanding of the research issues associated with these sensitive areas of cloud computing may enable us to better leverage benefits of the cloud and reflect on future possibilities of exploration.