Biblio

Reliable and scalable storage systems are key to cloud-based applications. In cloud storage, users store their data on remote servers rather than their local computers. Secure storage is used to ensure the safety of data in clouds. As more and more users rely on third-party cloud vendors to store their data, concerns have arisen among users and cloud providers. Encryption-based approaches are commonly used in secure storage systems. Data are encrypted and stored on persistent storage like disks and flash memories. When data are needed by the users, they are decrypted and accessed by the users. This way of managing data hurts the scalability and throughput of cloud systems. In the meantime, cloud systems have to perform fault-tolerance strategies on data, which also brings performance deduction. The combination of these issues cause a high price for data security in cloud systems. Aware of such issues. we propose methods to reduce the overhead of secure storage while guaranteeing the safeness of data.

High-accuracy localization is a prerequisite for many wireless applications. To obtain accurate location information, it is often required to share users' positional knowledge and this brings the risk of leaking location information to adversaries during the localization process. This paper develops a theory and algorithms for protecting location secrecy. In particular, we first introduce a location secrecy metric (LSM) for a general measurement model of an eavesdropper. Compared to previous work, the measurement model accounts for parameters such as channel conditions and time offsets in addition to the positions of users. We determine the expression of the LSM for typical scenarios and show how the LSM depends on the capability of an eavesdropper and the quality of the eavesdropper's measurement. Based on the insights gained from the analysis, we consider a case study in wireless localization network and develop an algorithm that diminish the eavesdropper's capabilities by exploiting the reciprocity of channels. Numerical results show that the proposed algorithm can effectively increase the LSM and protect location secrecy.