Cloud storage has been gaining tremendous popularity, which provides facilitative data storage and sharing services for distributed clients. To maximize the availability and reliability, some customers may store multiple replicas of critical data on cloud servers. However, cloud servers may collude to make it look like they are storing multiple copies of data, whereas in fact they only store a single copy. Currently, several multi-replica provable data possession schemes have been proposed to provide verifications to ensure that all the outsourced copies are actually stored and maintained intact. For these schemes with third-party verifications, correctly choosing public keys of data owners relies on Public Key Infrastructure (PKI), which is complicated and resource consuming. In this paper, we propose a novel identity-based public multi-replica provable data possession scheme, namely IDPMR-PDP, to provide third-party verification of outsourced data with multiple replicas without PKI. We also introduce a formal security model of identity-based public multi-replica PDP schemes and prove that IDPMR-PDP is secure against malicious cloud servers and privacy-preserving against curious verifiers under this model. Meanwhile, our analyses and simulation results demonstrate that IDPMR-PDP realizes efficient integrity verification.

The epoch of the Internet of Things (IoT) has come by enabling almost everything to gather and share electronic information. Considering the unreliable factors of public IoT, how to outsource huge amounts of indispensable stream data generated by the nodes to the remote storage (RS) efficiently and securely is one of the most challenging issues. In this article, we propose a secure lightweight stream data outsourcing framework for IoT based on identity and blockchain. Taking advantage of identity-based cryptography and blockchain, for public IoT containing untrusted communication channels, nodes, RS, and even verifiers, we introduce a private mobile network and multiple verifiers to ensure that the stream data are stored intact and updated correctly, without the costs and risks brought by the public-key infrastructures (PKI). Meanwhile, the framework can also achieve privacy-preserving checking, by revealing no data to the other entities besides the RS, even in the blockchains. Our comprehensive analysis and experiments demonstrate that the proposed framework is suitable for lightweight devices and practical for IoT.

Verifiable databases (VDB) enables the data owner to outsource a huge unencrypted database to the powerful but untrusted cloud such that any client could later retrieve the database and check whether the cloud returns valid records or not. To the best of our knowledge, there is no prior work considering privacy. Besides, they assume that the data owner and the client are fully trusted while they may be semi-honest in the real world. To address these problems, we propose a new primitive called privacy-preserving publicly verifiable database (PPVDB), which not only guarantees the integrity of the query result but also leaks no information. At the end of this protocol, the client can check whether the cloud returns a valid result and learns the query result but nothing else about the database. Besides, the cloud learns nothing about the database and the query, and the data owner does not know which item that the client has queried. Motivated by the comparison among some strawman solutions, we incorporate verifiable computation for the polynomial with oblivious pseudorandom function to construct a PPVDB scheme, which is the first VDB scheme providing stronger security against the malicious cloud and the semi-honest client and data owner.

Private set intersection (PSI) allows two parties to compute the intersection of their private sets while revealing nothing except the intersection. With t