Ensuring the integrity of outsourced data is one of several functional requirements in cloud storage services, although designing an effective and secure public auditing scheme remains an ongoing research challenge. For example, a number of existing schemes are designed based on symmetric bilinear pairing, which are computationally expensive. While certificate-based auditing schemes can simplify certificate management and mitigate key escrow concern, such schemes are not popular in the literature. Therefore, we propose a lightweight certificate-based public/private auditing scheme based on asymmetric bilinear pairing for cloud storage. Specifically, we describe a new method of designing lightweight auditing schemes. Additionally, our proposed scheme is proven to be secure in the random oracle model. We then implement our scheme by using type D curve of the pairing-based library. The findings demonstrate that our auditing scheme significantly reduces client’s computation cost in the tag-generation (TagGen) phase, particularly in comparison to several other competing schemes. For example, when the block size is 10 KB, our on-line computation cost in the TagGen phase takes only 0.45 seconds, while it requires at least 62.83 seconds in other schemes. Furthermore, the findings show that when the number of blocks is fixed, the on-line computation cost in our TagGen phase is constant despite varying file sizes.

With the development of cloud storage, how to protect the integrity of the data stored in the cloud becomes the clients' major concern. Recently, Zhang et al. proposed a certificateless data integrity auditing scheme for cloud-assisted cyber-physical-social systems. However, we find that their scheme has some security flaws, i.e., if a client outsources a file with m blocks data and tags, the cloud server can store only one block of them, and pass the integrity auditing of the auditor. We refer to this attack as storing one block attack. Then, we give an improved scheme to amend these flaws.

With the development of smart grid, the introduction of blockchain technology provides a novel idea for secure power data sharing. The existing blockchain-based data aggregation schemes generally rely on a unique leader node to perform verification algorithms, but there may be a lazy leader node not performing aggregation data verification to save computation costs. In addition, in the existing verification mechanism, light nodes need to perform the same verification operations as the leader node, which results in resource-constrained light nodes being unable to bear. In this paper, we propose an efficient blockchain-based data aggregation scheme with privacy-preserving on the smart grid, called EC-ASPG, which implements a supervised mechanism for the lazy leader node, enhancing the security of the system. Furthermore, we propose a separable consensus verification mechanism, which can prevent other light nodes from performing duplicate verification operations like the leader node, effectively improving the efficiency of consensus verification. Finally, we present a formal security proof and comprehensive performance evaluations. The results show that our scheme is secure and outperforms the compared schemes in terms of performance analysis.

To ensure the reliability and integrity of data in the cloud storage server, some scholars provided various data integrity auditing schemes. However, the most existing data integrity auditing schemes only support the static data and may be unsuitable for the dynamic operations of data. To overcome this difficulty, we propose a fuzzy identity-based dynamic auditing of big data, which combines the structure of the Merkle hash tree (MHT) with the Index logic table (ILT). Our scheme not only performs the dynamic operations of data block in the ILT, namely modification, insertion and deletion, but also efficiently executes dynamic operations of the ILT on the structure of the MHT. We also elaborate the security, characteristics and performance analysis of the proposed scheme separately. The analysis results show that the proposed scheme costs less time than the structure of the original MHT to generate the root node hash value during the metadata generation phase and update the root node hash value during the dynamic operations. Furthermore, when users store the new ILT in local storage, they require lower communication cost to update root node hash value than users without storing the ILT, and fewer interactions between the cloud storage server and users in the dynamic operations process.

Data integrity protection, an important feature in cloud storage services, can be achieved using auditing schemes. However, existing public and private auditing schemes are somewhat inefficient in practice. For example, in private auditing schemes, the trusted third-party is generally not able to settle disputes between users and the cloud storage server. In most existing public auditing schemes, it takes a user tens of seconds to generate data tags for every MB of file outsourced, which is clearly impractical particularly on resource-constrained end devices. Since the user is likely to have information than the auditor, we divide the verification phase into private verification and public verification phases. Then, we propose a public/private auditing model and a security model for public/private auditing. In our public/private auditing model, the user uses private verification phase to audit outsourced data promptly in most cases, and the auditor uses public verification phase to audit outsourced data only when dispute occurs or the user is not available to audit. Then, we propose a public/private auditing scheme, and present its security proof in the random oracle model under the discrete logarithm assumption. Experimental findings demonstrate that our scheme only need tens of microseconds to generate data tags for every MB file outsourced. In other words, the efficiency of our scheme is almost as high as existing high-performing private auditing schemes, and our scheme is more effective in comparison to existing efficient public auditing schemes.

To ensure the security of image information and facilitate efficient management in the cloud, the utilization of reversible data hiding in encrypted images (RDHEIs) has emerged as pivotal. However, most existing RDHEI schemes suffer from lower security and limited embedding capacity. To tackle these challenges, we propose a reversible data hiding (RDH) with secret encrypted image sharing and adaptive coding scheme. Specifically, in the encryption phase, we introduce an improved secret sharing (SS) encryption method based on the Chinese remainder theorem for polynomials (CRTPs). This method not only improves the security of encrypted images but also vacates a larger room for embedding. In the embedding phase, we introduce an adaptive coding embedding approach using xor preservation (XORP) and huffman coding, which provides high embedding capacity. Experimental results and security analysis demonstrate that our proposed encryption method achieves optimal values in security indicators for encrypted images, such as information entropy, histograms, number of pixels change rate and unified average changing intensity. The proposed embedding method is superior to some state-of-the-art schemes in terms of embedding capacity. Furthermore, in datasets BOSSBase and BOWS2, the average embedding rates of the proposed embedding approach can reach 2.1745 bits per pixel (bpp) and 2.0656 bpp, respectively.