In emerging cloud computing, a central application is to outsource the files and record belonging to its user, to outer cloud servers for adaptable information storage. The outsourced documents and files should be encrypted because of the protection and secrecy worries of their proprietor. As there is large amount data present in the cloud it is very important to have a multi-keyword search over the encrypted data. Essentially huge amount of data is present on cloud and providing it for any time on demand request is difficult and is challenging. As searching is time consuming process it is important to provide multi keyword search giving a ranking result to get effective data. To maintain accuracy of search result and also provide better searching experience, it is important for such ranking system to provide multiple keyword searches, as single keyword search gives lots of noisy data. However, for privacy requirement encryption should be done on the sensitive data before outsourcing it, which obsoletes data utilization like information retrieval based on keyword. The main goal of efficient and secure search is building up the searchable encryption for multi-keyword ranked search over the scalable data documents that are stored on cloud.

No abstract

No 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.