Data deduplication contributes to avoiding great waste of cloud storage resources. Most of current data deduplication schemes focus on file-level data deduplication, without realizing deduplication ownership privacy protection, data blocks retrieval or error data blocks recovery. To this end, this paper proposes cross-clouds encrypted data fine-grained deduplication and recovery (CC-FGDR) scheme supporting blockchain collaborative computing. CC-FGDR exploits two-party joint generation of deduplication tags to prevent deduplication privacy leakage, and constructs vector-commitment ciphertext tree to realize proofs of ownership verification of distributed backup data blocks via blockchain systems. CC-FGDR achieves secure cross-clouds deduplication detection by constructing twin bloom filter tree and privacy puncture pseudo-random function. To achieve data availability, a ciphertext reconstruction matrix is introduced and combined with countable bloom filter to achieve the location, search and retrieval of distributed outsourced data blocks. CC-FGDR further designs low-density parity check code to achieve cross-clouds encrypted error data recovery through collaborative computing of smart contracts. The security analysis demonstrates CC-FGDR ensures data storage verifiability, data confidentiality, and ownership privacy protection. Performance evaluation demonstrates the feasibility of CC-FGDR in the deployment of multiple clouds via blockchain systems, and CC-FGDR significantly improves the deduplication efficiency by joint deduplication in multi-clouds.

With the increasing prevalence of network cloud storage, an escalating number of users are choosing to entrust their data to the cloud. To guarantee remote data integrity and mitigate irreversible loss in case of a single point of failure, numerous multi-cloud public auditing schemes have been proposed. However, most existing studies primarily focus on storage architectures with multiple copies. In practice, users are required to distribute identical data replicas individually across multiple cloud servers (CSs), resulting in significant communication overhead and substantial consumption of storage resources on these servers. Moreover, there is a lack of secure public auditing schemes that effectively address both fault localization and data recovery challenges. To address these issues and enhance storage data reliability, this paper proposes an identity-based integrity auditing and data recovery scheme with fault localization for multi-cloud storage (hereafter referred to as IB-IADR). Specifically, we design a novel identity-based homomorphic signature to facilitate a lightweight auditing challenge-verification process. Our scheme ensures the uniform distribution of encoded data while minimizing data redundancy across multiple CSs. Additionally, IB-IADR provides robust data recovery capabilities and supports fast and accurate fault localization features, including entity position, file position and data block position. We demonstrate that our scheme is provably secure against forgery attacks on response auditing proofs, based on the hardness assumption of the standard CDH problem and DDH problem. We evaluate the proposed scheme’s performance to demonstrate its utility in multi-cloud storage environments.

Compared to conventional wireless body area networks (WBANs), the amount of data processed and the analytical capabilities offered by cloud-based WBANs are significantly more extensive. Nevertheless, the paramount consideration in such contexts remains the security and privacy ramifications. Concurrently, the process where medical cloud server (MCS) computes the response aggregation data may be opaque and there is a risk that (partially) invalid aggregation results may be presented to the task requester, either intentionally (e.g., malicious or cost-saving) or unintentionally (e.g., corruption or processing error). Furthermore, with the different roles played by each data requester, relying solely on a single data aggregation type is no longer sufficient to satisfy the diverse data aggregation requests from these requesters. To this end, this paper proposes a novel verifiable multi-dimensional encrypted medical data aggregation scheme (VMEMDA) for cloud-based WBANs, where we integrate an extended super-increasing sequence with a modified Paillier cryptosystem. Doing so allows us to ensure that each dimensional medical data collected by wireless sensor devices and corresponding square values can be encrypted into a single ciphertext with the chronological time series. This enables MCS to select various aggregation types, such as spatial/temporal data aggregation, to aggregate the multi-source encrypted medical data into a single ciphertext. Then the task requester can conduct diverse privacy-preserving statistical analyses, including sum, average, and variance. Moreover, we utilize a homomorphic hash function to guarantee the encrypted data integrity in a highly efficient way, and we design an unpredictable random sequence and integrate it into the provable data possession mechanism to achieve aggregated data correctness guarantee. Performance evaluation demonstrates that VMEMDA exhibits considerably lower computation and communication overhead compared to other existing multi-dimensional data aggregation schemes.

Smart grid is widely deployed in the modern smart city. However, the frequent network attacks on smart grid today have raised concerns about the privacy and security of individual fine-grained information collection. Moreover, once the secret key held by the data control center is disclosed, any adversary could easily break the indistinguishability of ciphertexts, thereby revealing users privacy. To this end, we propose an enabling efficient multidimensional encrypted data aggregation scheme for fog-cloud-based smart grid by using the improved Boneh-Goh-Nissim cryptosystem and the super-increasing vector technique, which can realize efficient multi-source multidimensional encrypted data aggregation in the fog-cloud architecture. The security analysis demonstrates that our scheme can satisfy security requirements of smart grid, i.e. it achieves the usage data privacy protection and confidentiality, multidimensional aggregation data integrity, and key-disclosure resistance. The performance evaluations show that our scheme is more efficient than related data aggregation schemes.

Public verification enables cloud users to employ a third party auditor (TPA) to check the data integrity. However, recent breakthrough results on quantum computers indicate that applying quantum computers in clouds would be realized. A majority of existing public verification schemes are based on conventional hardness assumptions, which are vulnerable to adversaries equipped with quantum computers in the near future. Moreover, new security issues need to be solved when an original data owner is restricted or cannot access the remote cloud server flexibly. In this paper, we propose an efficient identity-based data outsourcing with public integrity verification scheme (DOPIV) in cloud storage. DOPIV is designed on lattice-based cryptography, which achieves post-quantum security. DOPIV enables an original data owner to delegate a proxy to generate the signatures of data and outsource them to the cloud server. Any TPA can perform data integrity verification efficiently on behalf of the original data owner, without retrieving the entire data set. Additionally, DOPIV possesses the advantages of being identity-based systems, avoiding complex certificate management procedures. We provide security proofs of DOPIV in the random oracle model, and conduct a comprehensive performance evaluation to show that DOPIV is more practical in post-quantum secure cloud storage systems.

Wireless body area networks (WBANs) rely on powerful cloud storage services to manage massive medical data. As precise medical diagnosis analysis is heavily based on these medical data, any altered medical data may cause severe consequences, the integrity of outsourced medical data has become the most concerning security issue. Up to date, most existing public auditing mechanisms have been proposed to check the data integrity, but they could not achieve conditional identity privacy, any patient would not like others to know his/her real identity corresponding to certain serious disease, and some malicious patients should be revoked timely due to misbehaviors. Additionally, they are vulnerable to malicious auditors, by colluding with the cloud server to cheat patients. In this paper, we propose a conditional identity privacy-preserving public auditing (CIPPPA) mechanism for cloud-based WBANs. CIPPPA is the first public auditing mechanism achieving conditional identity privacy of patients in WBANs, the real identity of a patient is unknown to anyone in cloud-based WBANs other than the private key generator (PKG). We attempt to integrate Ethereum blockchain into CIPPPA, which gives assistance to patients for validating malicious auditing behaviors. Formal security analysis and performance evaluation demonstrate that CIPPPA is practical for cloud-based WBANs.