A Critical Survey on Privacy Prevailing in Mobile Cloud Computing: Challenges, State of the Art Methods and Future Directions

Abstract

With the explosive growth of mobile applications and extensive praxis of cloud computing, mobile cloud computing has been introduced to be a potential technology for mobile services. But privacy is the main concern for a mobile user in the modern era. In the current study, we address the privacy challenges faced by mobile users while outsourcing their data to the service provider for storage and processing. However, a secure mobile user is required to protect these fundamental privacy factors such as their personal data, real identity, current location and the actual query sent to the cloud vendor server while availing different cloud services. Under these privacy metrics, we evaluated the existing approaches that are counting privacy challenge in mobile cloud computing. The primary focus of this study is to presents a critical survey of recent privacy protection techniques. Leading to objective, the current study conduct a comparative analysis of these state of the art methods with their strong points, privacy level and scalability. After analysis, this paper suggests the pseudo-random permutation method could be a promising solution that can be taken into consideration for preserving user personal information and data query privacy in MCC more efficiently. Primarily, the purpose of the survey was to focus on further advancements of the suggested method. Furthermore, we present the future research directions in the mobile cloud computing paradigms.