Data Sharing Scheme Research Articles

A Certificateless Threshold Proxy Re-Encrypted Data-Sharing Scheme With Cloud-Chain Collaboration in Industrial Internet Environments

A Certificateless Threshold Proxy Re-Encrypted Data-Sharing Scheme With Cloud-Chain Collaboration in Industrial Internet Environments

Blockchain-enabled data sharing for IoT: A lightweight, secure and searchable scheme

With the popularity of Internet of Things (IoT) applications, data sharing among IoT devices has become more frequent. Many researchers have proposed fine-grained access control schemes and searchable encryption algorithms to support privacy-preserving data sharing. But there still exist two challenges. First, the existing schemes are computationally intensive, making them unsuitable for resource-limited IoT terminals. Second, they rely on a central server to honestly conduct search operations, making them unable to tackle malicious servers. To this end, we propose a blockchain-enabled data-sharing scheme for IoT that supports lightweight, secure, and searchable data sharing. We design an outsourcing attribute-based encryption algorithm to alleviate the overhead of resource-limited IoT terminals, which reduces the local encryption and decryption to a constant level. Instead of relying on central servers, we leverage smart contract to execute ciphertext retrieval, ensuring the accuracy of search results. Formal security analysis demonstrates that the proposed scheme is chosen-plaintext secure under the DBDH assumption. Experimental simulation shows that it reduces the search time by at least 79.9%, the encryption and decryption complexities to both O(1).

Anonymous data sharing scheme for resource-constrained internet of things environments

With the rapid development of Internet of Things (IoT) technology in industrial, agricultural, medical and other fields, IoT terminal devices face security and privacy challenges when sharing data. Among them, ensuring data confidentiality, achieving dual-side privacy protection, and performing reliable data integrity verification are basic requirements. Especially in resource-constrained environments, limitations in the storage, computing, and communication capabilities of devices increase the difficulty of implementing these security safeguards. To address this problem, this paper proposes a resource-constrained anonymous data-sharing scheme (ADS-RC) for the IoT. In ADS-RC, we use elliptic curve operations to replace computation-intensive bilinear pairing operations, thereby reducing the computational and communication burden on end devices. We combine an anonymous verifiable algorithm and an attribute encryption algorithm to ensure double anonymity and data confidentiality during the data-sharing process. To deal with potential dishonest behavior, this solution supports the revocation of malicious user permissions. In addition, we designed a batch data integrity verification algorithm and stored verification evidence on the blockchain to ensure the security and traceability of data during transmission and storage. Through experimental verification, the ADS-RC scheme achieves reasonable efficiency in correctness, security and efficiency, providing a new solution for data sharing in resource-constrained IoT environments.

An anonymous and large-universe data-sharing scheme with traceability for medical cloud storage

The application of medical cloud storage technology in healthcare and the sharing of electronic medical records (EMR) bring convenience for patients and medical institutes. However, two barriers limit further expansions of the above (i.e. key escrow and key abuse issues). In this paper, we construct a large universe data-sharing scheme based on attribute-based encryption. We design all attribute authorities simultaneously to participate in the key computation, and the user performs aggregation. By issuing anonymous credentials to the recipients, their identity information is protected. To achieve complete tracing of the traitor, we blend the two mechanisms, white-box traceability and black-box traceability, together. Detailed security proofs have been carried out for various types of possible attackers, and theoretical analyses have verified the security of the proposed scheme. We performed performance evaluations in conjunction with existing schemes, and numerical experience shows that the burden on the user side is also minimal.

HA-Med: A Blockchain-Based Solution for Sharing Medical Data with Hidden Policies and Attributes

Existing healthcare data-sharing solutions often combine attribute-based encryption techniques with blockchain technology to achieve fine-grained access control. However, the transparency of blockchain technology may introduce potential risks of exposing access structures and user attributes. To address these concerns, this paper proposes a novel healthcare data-sharing scheme called HA-Med. By leveraging blockchain technology, HA-Med ensures the concealment of access policies and attributes, providing a secure solution for fine-grained access control of medical data. Furthermore, the scheme supports attribute revocation and forward secrecy to enhance user privacy. The security of HA-Med is rigorously verified through theoretical analysis, and its feasibility is demonstrated through experiments conducted using the Java-based JPBC library.

Enhancing privacy in cyber–physical systems: An efficient blockchain-assisted data-sharing scheme with deniability

The data in Cyber–Physical Systems (CPSs) is currently undergoing an explosive surge. Blockchain-based CPS exhibit enhancements in security, fault tolerance, and trust for its data sharing. However, it is very challenging to achieve the privacy preserving and efficient data sharing in CPS considering the privacy concerns introduced by blockchain while the cost associated with privacy protection cannot be neglected. To release these potential challenges, we propose a blockchain-assisted data-sharing scheme that ensures security, privacy-preserving and efficiency. We introduce deniability into data-sharing based on an identity-based deniable authentication protocol. This protocol enables data owners to deny their data-sharing actions, thereby protecting their privacy, while simultaneously providing recipients with the assurance of data verifiability. Furthermore, by incorporating multi-recipient encryption techniques, the proposed scheme significantly simplifies interactions with multiple recipients, reducing associated costs. Additionally, we propose a source traceability mechanism with the assistance of blockchain, establishing a distributed, transparent and trustworthy framework for data sharing, while ensuring honest cooperation between the individual participants. Security analysis and performance comparisons demonstrate the effectiveness and security of this scheme.

Improving Security in the Internet of Vehicles: A Blockchain-Based Data Sharing Scheme

To ensure the aggregation of a high-quality global model during the data-sharing process in the Internet of Vehicles (IoV), current approaches primarily utilize gradient detection to mitigate malicious or low-quality parameter updates. However, deploying gradient detection in plain text neglects adequate privacy protection for vehicular data. This paper proposes the IoV-BDSS, a novel data-sharing scheme that integrates blockchain and hybrid privacy technologies to protect private data in gradient detection. This paper utilizes Euclidean distance to filter the similarity between vehicles and gradients, followed by encrypting the filtered gradients using secret sharing. Moreover, this paper evaluates the contribution and credibility of participating nodes, further ensuring the secure storage of high-quality models on the blockchain. Experimental results demonstrate that our approach achieves data sharing while preserving privacy and accuracy. It also exhibits resilience against 30% poisoning attacks, with a test error rate remaining below 0.16. Furthermore, our scheme incurs a lower computational overhead and faster inference speed, markedly reducing experimental costs by approximately 26% compared to similar methods, rendering it suitable for highly dynamic IoV systems with unstable communication.

A Blockchain-Based Privacy-Preserving Healthcare Data Sharing Scheme for Incremental Updates

With the rapid development of artificial intelligence (AI) in the healthcare industry, the sharing of personal healthcare data plays an essential role in advancing medical AI. Unfortunately, personal healthcare data sharing is plagued by challenges like ambiguous data ownership and privacy leakage. Blockchain, which stores the hash of shared data on-chain and ciphertext off-chain, is treated as a promising approach to address the above issues. However, this approach lacks a flexible and reliable mechanism for incremental updates of the same case data. To avoid the overhead of authentication, access control, and rewards caused by on-chain data changes, we propose a blockchain and trusted execution environment (TEE)-based privacy-preserving sharing scheme for healthcare data that supports incremental updates. Based on chameleon hash and TEE, the scheme achieves reliable incremental updates and verification without changing the on-chain data. In the scheme, for privacy concerns, off-chain data are protected through symmetric encryption, whereas data verification, decryption, and computation are performed within TEE. The experimental results show the feasibility and effectiveness of the proposed scheme.

Secure Data Sharing Scheme for Multi-Node Devices

For the problem that the communication between maritime devices may be listened to by the adversary, resulting in the data shared between maritime devices may also be tampered with and forged by the adversary, thus jeopardizing the maritime IoT, this paper firstly starts from the wireless sensor network technology which is the most widely used in the maritime IoT, and then selects and designs a lightweight block cipher algorithm for realizing the secure data sharing of the multi-node devices in the maritime IoT. After analyzing the security of the algorithm, it is concluded that this paper's scheme performs well in terms of anti-differential analysis and linear analysis, and is better than PRESENT algorithm in terms of hardware implementation.

A Privacy-Preserving User-Centric Data-Sharing Scheme

A Privacy-Preserving User-Centric Data-Sharing Scheme

BE-TRDSS: Blockchain-Enabled Secure and Efficient Traceable-Revocable Data-Sharing Scheme in Industrial Internet of Things

As an important component of the industrial Internet of Things (IIoT), the smart factory uses IIoT and equipment-monitoring technology to collect data to reasonably arrange production. A large number of data is collected and uploaded to the IIoT cloud platform. However, the IIoT cloud platform is semi-trusted and has structural limitations and vulnerability, which makes it necessary to realize data dynamic security sharing and malicious users tracking. In this paper, we show that most recent work on this issue is still vulnerable to security threats at first. Then a blockchain-enabled dynamic and traceable data-sharing scheme for a smart factory is proposed. Blockchain performs the user authentication and stores the ciphertext index and public keys to avoid tampering with shared data. The tracking algorithm tracks malicious users and adds them to a revocation list embedded in the ciphertext. And the authority can flexibly select domain or user revocation as required. The LSSS access policy is hidden to protect user privacy, and the cloud server uses match test algorithm to detect whether users meet hidden access policy. Additionally, online-offline encryption and outsourced decryption improve the efficiency of the scheme where the ciphertext and the pairing operations required for decryption achieve constant size. A performance analysis shows that the scheme can resist a variety of collusion attacks, and simulations show that it outperforms current schemes.

Blockchain localization cloud computing big data application evaluation method

Abstract Blockchain technology is a widely used emerging technology. It can integrate cloud computing technology and big data to form a distributed cloud computing system, providing efficient services for local enterprises and governments. In addition, local cloud computing is also widely used, and there are many big data in these applications. Blockchain and local cloud computing technology offers safe and reliable information exchange for data exchange and provides a practical method for analyzing big data. This article aims to study how to analyze and research the application analysis method of big data based on blockchain technology and improve the classical apriori algorithm (CAA). This article compares and analyzes the performance of CAA and improved apriori algorithm (IAA) in big data applications. When the number of key words in the query are 20 and 100, the result search time of the CAA are 1.08 and 9.24 s, respectively, and the IAA are 0.76 and 7.58 s, respectively. The result search cost of the CAA is 12.43 and 91.55 kB, respectively, and the IAA is 5.05 and 63.72 kB, respectively. It is not difficult to see that applying the IAA to the blockchain-based government data-sharing scheme had relatively excellent performance and was worth further promotion and application.

Blockchain-Based Two-Stage Federated Learning With Non-IID Data in IoMT System

The Internet of Medical Things (IoMT) has a bright future with the development of smart mobile devices. Information technology is also leading changes in the healthcare industry. IoMT devices can detect patient signs and provide treatment guidance and even instant diagnoses through technologies, such as artificial intelligence (AI) and wireless communication. However, conventional centralized machine learning approaches are often difficult to apply within IoMT devices because of the difficulty of large-scale collection of patient data and the potential risk of privacy breaches. Therefore, we propose a blockchain-based two-stage federated learning approach that allows IoMT devices to train a global model collaboratively without gathering the data to a central server. Specifically, to address the problem of poor training performance on non-independent identically distributed (non-IID) data, we design a blockchain-based data-sharing scheme that can significantly improve the model’s accuracy without threatening user privacy. We also design a client selection mechanism to further improve the system’s efficiency. Finally, we validate the feasibility and effectiveness of our system through simulation experiments on three popular datasets (i.e., MNIST, Fashion-MNIST, and CIFAR-10).

OWL: A data sharing scheme with controllable anonymity and integrity for group users

As our society becomes digital and communication technology develops, global collaboration is an inevitable trend, where data-sharing is a critical component of cooperation across organizations. Identity privacy and data integrity are vital issues in data-sharing. Existing works struggle to address these problems simultaneously, either privacy leaking or privacy abuse. In this work, we proposed OWL, a data-sharing scheme that (1) provides users on-demand anonymity and (2) allows users to verify data integrity while preserving anonymity. To achieve (1) OWL enables controllable anonymity that allows de-anonymity for the malicious while keeping anonymity to the honest providers based on traceable ring signature technology. To achieve (2), OWL designs a data integrity auditing scheme that uses vector commitment to verify data integrity without privacy leakage. Furthermore, OWL employs the blockchain to store immutable auxiliary information for the integrity and controllable anonymity. We also employ the state channel to resolve the performance bottleneck of blockchain and design methods to improve the usage of the state channel for group users. We prove that OWL achieves controllable anonymity and integrity. Finally, we implement the experiment to evaluate the efficiency of OWL.

A Secure Data-Sharing Scheme for Privacy-Preserving Supporting Node–Edge–Cloud Collaborative Computation

The node–edge–cloud collaborative computation paradigm has introduced new security challenges to data sharing. Existing data-sharing schemes suffer from limitations such as low efficiency and inflexibility and are not easily integrated with the node–edge–cloud environment. Additionally, they do not provide hierarchical access control or dynamic changes to access policies for data privacy preservation, leading to a poor user experience and lower security. To address these issues, we propose a data-sharing scheme using attribute-based encryption (ABE) that supports node–edge–cloud collaborative computation (DS-ABE-CC). Our scheme incorporates access policies into ciphertext, achieving fine-grained access control and data privacy preservation. Firstly, considering node–edge–cloud collaborative computation, it outsources the significant computational overhead of data sharing from the owner and user to the edge nodes and the cloud. Secondly, integrating deeply with the “node–edge–cloud” scenario, the key distribution and agreement between all entities embedded in the encryption and decryption process, with a data privacy-preserving mechanism, improve the efficiency and security. Finally, our scheme supports flexible and dynamic access control policies and realizes hierarchical access control, thereby enhancing the user experience of data sharing. The theoretical analysis confirmed the security of our scheme, while the comparison experiments with other schemes demonstrated the practical feasibility and efficiency of our approach in node–edge–cloud collaborative computation.

Accountable Attribute-Based Data-Sharing Scheme Based on Blockchain for Vehicular Ad Hoc Network

Vehicular ad hoc network (VANET), as one of the bases of intelligent transport systems, plays an essential role in improving road traffic safety. Nevertheless, in such a complicated, distributed, and highly mobile network structure, how to achieve secure data sharing is a great challenge. The ciphertext-policy attribute-based encryption (CP-ABE) is a potential method to realize one-to-many data sharing for VANET. However, the key abuse problems of users and attribute authorities (AAs) incur many security concerns for VANET. Both issues are extremely important because the attribute keys directly affect users’ access to shared data. To solve the above issues, we propose an accountable attribute-based data-sharing scheme with the blockchain technology (AT-DS-VAHN, in short). For AAs key abuse, we use the consortium blockchain maintained by AAs to achieve distributed key storage and distribution. The attribute keys generated by each AA and its key distribution records are recorded on the blockchain in the form of transactions. Based on the traceability of blockchain, the key abuse behavior of AAs can be caught and prosecuted. For user key abuse, we achieve white-box traceability and efficient user revocation. Based on the principle of traceable-then-revocable, malicious users can be tracked and then revoked directly from the system without complex operations. Besides, to reduce the computation burden on users, our proposal supports online/offline encryption and verifiable outsourced decryption. Security and efficiency analyses show that our proposal is secure and efficient, with high practicability and reliability for VANET.

A blockchain-based traceable and secure data-sharing scheme.

The traditional data-sharing model relies on a centralized third-party platform, which presents challenges such as poor transaction transparency and unsecured data security. In this article, we propose a blockchain-based traceable and secure data-sharing scheme. Firstly, we designed an attribute encryption-based method to protect data and enable fine-grained shared access. Secondly, we developed a secure data storage scheme that combines on-chain and off-chain collaboration. The InterPlanetary File System (IPFS) is used to store encrypted data off-chain, and the hash value of encrypted data is stored on the blockchain. To improve data security, elliptic curve cryptography (ECC) encryption is performed before the hash value is stored. Finally, we designed a smart contract-based log tracking mechanism. The mechanism stores data sharing records on the blockchain and displays them in a visual form to meet the identity tracking needs of both data sharing parties. Experimental results show that our scheme can effectively secure data, track the identities of both parties sharing data in real-time, and ensure high data throughput.

Blockchain-Based Anonymous Data Sharing With Accountability for Internet of Things

Blockchain has been a promising infrastructure for enabling secure data sharing for the Internet of Things (IoT). With the widespread of IoT applications, security issues, such as data privacy, anonymity, and accountability become critical concerns for the users, which are essential principles for secure communication in those applications. However, the existing blockchain-based data-sharing schemes mainly consider data privacy. Only a few works can support anonymity with strong, trusted assumptions. Thus, there is a research gap on the anonymity of blockchain-based data sharing for IoT, which does not rely on any trusted party. In this article, we propose a blockchain-based anonymous data-sharing scheme (BA-DS) by adopting a novel public key encryption derived from a ring signature. In BA-DS, we remove the trusted party and ensure anonymity by using an unconditional linkable ring signature and Signature of Knowledge (SoK). During the revocation, we apply blockchain infrastructure to record the valid revocation list and generate a tag for data stored on the cloud, providing solid accountability. The formal security analysis shows that BA-DS is selective indistinguishable secure in the random oracle model. Additionally, we also prove that BA-DS holds anonymity, data privacy, accountability, and authenticity. The extensive experiments indicate that our proposed BA-DS achieves reasonable efficiency in terms of computational complexity, communication overhead, and consumption on the blockchain.

IP for Sharing and Opening Government Data Based on Big Data

With the continuous application and popularization of big data technology, all government departments are aware of the importance of data as a national basic strategic resource, and all over the country have been promoting the sharing and opening (SOA) of local government data (GA) one after another, improving the organization, formulating government regulations, and building a GA SOA platform. At present, GA are kept separately in each department, while there is no good DS scheme, resulting in low data sharing (DS), lack of authenticity of shared data, easy leakage of data, and difficulty in data tracking. Through the analysis of the above problems, an integrated platform(IP) of GA SOA based on big data is designed, aiming to realize safe and controlled sharing of GA. The application of this platform helps to efficiently integrate data resources and maximize the realistic value of GA for people's services in order to achieve sustainable social development.

A Privacy-Preserving Medical Data Sharing Scheme Based on Blockchain.

With the increasing penetration of the Internet of things (IoT) into people's lives, the limitations of traditional medical systems are emerging. First, the typical way of handling sensitive information can easily lead to privacy disclosure. Second, the medical system is relatively isolated. It is difficult for one medical system to share data with another, and the scope of users' activities is limited within the system boundary. To solve these two problems, we propose a new privacy-preserving medical data-sharing scheme by introducing the authorization mechanism and attribute-based encryption (ABE) based on blockchain, which breaks system boundaries and realizes data sharing among several medical institutions. ABE is used to realize scalable access control. In addition, doctors can share their knowledge to diagnose users by introducing many-to-many matching, which means that patients' health data can be represented by multiple keywords and doctors' expertise can be represented by multiple interests. We provide the correctness and security analysis of our scheme and implement a prototype tool on Ethereum. The experimental results show that our scheme solves the contradiction between the privacy preservation of medical data and the necessity of data sharing.