Practical blacklist-based anonymous authentication scheme for mobile crowd sensing

Abstract

Mobile crowd sensing (MCS) represents one of the most promising approaches for improving life quality of individuals with sensing and computing devices. MCS is playing a more and more important role in various fields of service, such as traffic monitoring and commercial advertisement. Security and privacy of communication in MCS attract increasing attention from the academia and industry since the sensing data are usually sensitive for users. Some users worry about the leakage of their private information when they share their data to the third parties. To address this issue, in this paper, we propose a practical blacklist-based anonymous authentication scheme in which users can enjoy an anonymous environment and share their information without worrying about any information leakage. Security analysis shows that our scheme can achieve anonymity, blacklistability, nonrepudiation and unlinkability. Performance evaluation demonstrates that our scheme is more efficient in terms of computation overhead compared with the existing works.