With the rapid advancement of technology, smart grid are increasingly replacing traditional grids. Smart grid offer efficient data management and analysis tools that significantly benefit users, but they also introduce new privacy challenges. Privacy-preserving data aggregation (PPDA) schemes have emerged as a solution, enabling the aggregation and processing of large-scale datasets without revealing any individual data points. This not only protects user privacy but also ensures data availability. In recent years, the field of smart grid privacy preservation has seen significant advancements in PPDA schemes. However, there has been a notable lack of comprehensive reviews that systematically summarize and analyze these developments. Our work aims to address this gap by providing a detailed survey of the latest PPDA schemes for smart grids over the past few years. This effort is intended to offer scholars a clear overview of the current state of the field and facilitate their understanding of the latest progress in smart grid privacy preservation. This paper provides a comprehensive survey of PPDA schemes for smart grid, analyzing their security requirements and discussing key implementation techniques. Based on whether the scheme relies on a trusted authority, we categorize the schemes into two main types. Schemes with a trusted authority are further divided into those that enhance increase data verifiable security, fault tolerance mechanisms, detect erroneous data, and support multi-type operations. In contrast, schemes without a trusted authority are classified into centralized architectures based on multiple nodes and decentralized architectures based on blockchain. This paper compares and analyzes the security, application scenarios, and performance of these schemes, and proposes future research directions based on the limitations of existing PPDA schemes.

With the rapid development of cloud storage and cloud computing technology, users tend to store data in the cloud for more convenient services. In order to ensure the integrity of cloud data, scholars have proposed cloud data integrity verification schemes to protect users’ data security. The storage environment of the Internet of Things, in terms of big data and medical big data, demonstrates a stronger demand for data integrity verification schemes, but at the same time, the comprehensive function of data integrity verification schemes is required to be higher. Existing data integrity verification schemes are mostly applied in the cloud storage environment but cannot successfully be applied to the environment of the Internet of Things in the context of big data storage and medical big data storage. To solve this problem when combined with the characteristics and requirements of Internet of Things data storage and medical data storage, we designed an SM2-based offline/online efficient data integrity verification scheme. The resulting scheme uses the SM4 block cryptography algorithm to protect the privacy of the data content and uses a dynamic hash table to realize the dynamic updating of data. Based on the SM2 signature algorithm, the scheme can also realize offline tag generation and batch audits, reducing the computational burden of users. In security proof and efficiency analysis, the scheme has proven to be safe and efficient and can be used in a variety of application scenarios.

Cloud storage and cloud computing technologies have developed rapidly for a long time, and many users outsource the storage burden of their data to the cloud to obtain more convenient cloud storage services. Allowing users to audit the private data’s integrity has become an additional basic function of the cloud server when providing services. In 2021, based on the BLS signature and automatic blocker protocol, Jalil et al. proposed a secure and efficient cloud data auditing protocol. The protocol can realize public audit, batch audit, data update, and protect data privacy. Moreover, the automatic blocker protocol is used to realize the identity authentication of the auditor. The protocol is relatively novel, innovative, and has a larger use space. However, we found that their scheme had security problems. If the cloud server has thoughts of malicious attack, he can forge the proof that he holds users’ data with stored labels and pass the audit. Referring to the original protocol and being inspired by them, we propose an improved audit protocol. The improved protocol solves the security problem and is more effective.

With the surge in cloud storage popularity, more individuals are choosing to store large amounts of data on remote cloud service providers (CSPs) to save local storage resources. However, users’ primary worries revolve around maintaining data integrity and authenticity. Consequently, several cloud auditing methods have emerged to address these concerns. Many of these approaches rely on traditional public-key cryptography systems or are grounded in identity-based cryptography systems or certificateless cryptography systems. However, they are vulnerable to the increased costs linked with certificate management, key escrow, or the significant expenses of establishing a secure channel, respectively. To counter these limitations, Li et al. introduced a certificate-based cloud auditing protocol (LZ22), notable for its minimal tag generation overhead. Nonetheless, this protocol exhibits certain security vulnerabilities. In this paper, we devise a counterfeiting technique that allows the CSP to produce a counterfeit data block with an identical tag to the original one. Our counterfeiting method boasts a 100% success rate ∀ data block and operates with exceptional efficiency. The counterfeiting process for a single block of 10 kB, 50 kB, and 100 kB takes a maximum of 0.08 s, 0.51 s, and 1.04 s, respectively. By substituting the exponential component of homomorphic verifiable tags (HVTs) with non-public random elements, we formulate a secure certificate-based cloud auditing protocol. In comparison to the LZ22 protocol, the average tag generation overhead of our proposed protocol is reduced by 6.80%, 13.78%, and 8.66% for data sizes of 10 kB, 50 kB, and 100 kB, respectively. However, the auditing overhead of our proposed protocol shows an increase. The average overhead rises by 3.05%, 0.17%, and 0.45% over the LZ22 protocol’s overhead for data sizes of 10 kB, 50 kB, and 100 kB, correspondingly.

Smart grid can be effectively enhanced by user data, however, data breaches pose significant risks related to privacy violations and data misuse. To address this issue, fault-tolerant privacy-preserving data aggregation schemes can protect data privacy while accommodating user drops. Most existing solutions depend on auxiliary computation in trusted authority for data aggregation. However, for practical smart grid applications, it is often unrealistic to expect these centers to remain online at all times. Designing a solution that does not rely on trusted authority (TA) while ensuring fault tolerance is a challenging task. In this paper, we propose an enabling efficient and fault-tolerant data aggregation scheme without TA, named EEFDA. Unlike existing encryption schemes, EEFDA supports reusable masks. We introduce the Reusable Shamir Threshold Secret Sharing (RSSS) technique, which allows users to securely adjust the secret without disclosing the initial sharing. The EEFDA scheme not only enhances system robustness but also reduces the communication overhead for inter-user interactions. Numerous experiments demonstrate that EEFDA communication is low-cost, efficient, and well-suited for resource-constrained devices.

Cloud storage technology is evolving at a high speed; effectively auditing the cloud data’s integrity has become a focal point. Recently, Ming and Shi proposed a certificateless integrity auditing scheme with a privacy protection function. The scheme used the certificateless cryptosystem to solve the certificate management problem of the auditing schemes based on public key infrastructure and the key escrow problem of the identity-based auditing schemes. Although their scheme is novel and efficient, we found that their scheme was not secure and could not achieve integrity auditing of cloud data. The malicious cloud server can generate the proof through the blocks and tags sent by the user. On the basis of the original scheme, we propose an improved auditing scheme; our new scheme is more secure and effective. In addition, for the problem of idle tags in the existing cloud data integrity auditing scheme, we propose the idea of intermediate tags and we applied the idea to the improved scheme to improve audit efficiency.