Su Jin Shin¹, Sang Uk Shin^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.2, pp. 2787-2819, 2025, DOI:10.32604/cmes.2025.072602 - 26 November 2025

Abstract To reconstruct vehicle accidents, data from the time of the incident—such as pre-collision speed and collision point—is essential. This data is collected and generated through various sensors installed in the vehicle. However, it may contain sensitive information about the vehicle owner. Consequently, vehicle owners tend to be reluctant to provide their vehicle data due to concerns about personal information exposure. Therefore, extensive research has been conducted on secure vehicle data trading models. Existing models primarily utilize centralized approaches, leading to issues such as single points of failure, data leakage, and manipulation. To address these problems,… More >

Xiaohui Yang, Shuo Huang^*

CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 5071-5089, 2025, DOI:10.32604/cmc.2025.061507 - 19 May 2025

Abstract With the rapid development of medical data sharing, issues of privacy and ownership have become prominent, which have limited the scale of data sharing. To address the above challenges, we propose a blockchain-based data-sharing framework to ensure data security and encourage data owners to actively participate in sharing. We introduce a reliable attribute-based searchable encryption scheme that enables fine-grained access control of encrypted data and ensures secure and efficient data sharing. The revenue distribution model is constructed based on Shapley value to motivate participants. Additionally, by integrating the smart contract technology of blockchain, the search More >

Shenjian Xiao¹, Xiaoli Qin¹, Yanzhao Tian^1,*, Zhongkai Dang²

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 2351-2373, 2025, DOI:10.32604/cmc.2025.062324 - 16 April 2025

Abstract The advent of the digital age has consistently provided impetus for facilitating global trade, as evidenced by the numerous customs clearance documents and participants involved in the international trade process, including enterprises, agents, and government departments. However, the urgent issue that requires immediate attention is how to achieve secure and efficient cross-border data sharing among these government departments and enterprises in complex trade processes. In addressing this need, this paper proposes a data exchange architecture employing Multi-Authority Attribute-Based Encryption (MA-ABE) in combination with blockchain technology. This scheme supports proxy decryption, attribute revocation, and policy update,… More >

Guoqiong Liao^1,3, Yinxiang Lei^1,2,*, Yufang Xie¹, Neal N. Xiong⁴

CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 3309-3335, 2025, DOI:10.32604/cmc.2024.060077 - 17 February 2025

Abstract As the Internet of Medical Things (IoMT) continues to expand, smart health-monitoring devices generate vast amounts of valuable data while simultaneously raising critical security and privacy challenges. Blockchain technology presents a promising avenue to address these concerns due to its inherent decentralization and security features. However, scalability remains a persistent hurdle, particularly for IoMT applications that involve large-scale networks and resource-constrained devices. This paper introduces a novel lightweight sharding method tailored to the unique demands of IoMT data sharing. Our approach enhances state bootstrapping efficiency and reduces operational overhead by utilizing a dual-chain structure comprising… More >

Youngho Park¹, Su Jin Shin², Sang Uk Shin^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.1, pp. 671-688, 2024, DOI:10.32604/cmes.2024.052378 - 20 August 2024

Abstract Data trading enables data owners and data requesters to sell and purchase data. With the emergence of blockchain technology, research on blockchain-based data trading systems is receiving a lot of attention. Particularly, to reduce the on-chain storage cost, a novel paradigm of blockchain and cloud fusion has been widely considered as a promising data trading platform. Moreover, the fact that data can be used for commercial purposes will encourage users and organizations from various fields to participate in the data marketplace. In the data marketplace, it is a challenge how to trade the data securely… More >

Iuon-Chang Lin¹, I-Ling Yeh¹, Ching-Chun Chang², Jui-Chuan Liu³, Chin-Chen Chang^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.1, pp. 809-822, 2024, DOI:10.32604/cmes.2024.051612 - 20 August 2024

Abstract Centralized storage and identity identification methods pose many risks, including hacker attacks, data misuse, and single points of failure. Additionally, existing centralized identity management methods face interoperability issues and rely on a single identity provider, leaving users without control over their identities. Therefore, this paper proposes a mechanism for identity identification and data sharing based on decentralized identifiers. The scheme utilizes blockchain technology to store the identifiers and data hashed on the chain to ensure permanent identity recognition and data integrity. Data is stored on InterPlanetary File System (IPFS) to avoid the risk of single More >

Qiuyan Wang, Haibing Dong^*, Yongfei Huang, Zenglei Liu, Yundong Gou

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 1967-1983, 2024, DOI:10.32604/cmc.2024.052775 - 15 August 2024

Abstract Sharing data while protecting privacy in the industrial Internet is a significant challenge. Traditional machine learning methods require a combination of all data for training; however, this approach can be limited by data availability and privacy concerns. Federated learning (FL) has gained considerable attention because it allows for decentralized training on multiple local datasets. However, the training data collected by data providers are often non-independent and identically distributed (non-IID), resulting in poor FL performance. This paper proposes a privacy-preserving approach for sharing non-IID data in the industrial Internet using an FL approach based on blockchain… More >

Yan Sun, Caiyun Liu, Jun Li, Yitong Liu^*

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2351-2362, 2024, DOI:10.32604/cmc.2024.048903 - 15 August 2024

Abstract With the development of technology, the connected vehicle has been upgraded from a traditional transport vehicle to an information terminal and energy storage terminal. The data of ICV (intelligent connected vehicles) is the key to organically maximizing their efficiency. However, in the context of increasingly strict global data security supervision and compliance, numerous problems, including complex types of connected vehicle data, poor data collaboration between the IT (information technology) domain and OT (operation technology) domain, different data format standards, lack of shared trust sources, difficulty in ensuring the quality of shared data, lack of data… More >

Siwan Noh¹, Kyung-Hyune Rhee^2,*

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 3805-3826, 2024, DOI:10.32604/cmc.2024.050949 - 20 June 2024

Abstract In Decentralized Machine Learning (DML) systems, system participants contribute their resources to assist others in developing machine learning solutions. Identifying malicious contributions in DML systems is challenging, which has led to the exploration of blockchain technology. Blockchain leverages its transparency and immutability to record the provenance and reliability of training data. However, storing massive datasets or implementing model evaluation processes on smart contracts incurs high computational costs. Additionally, current research on preventing malicious contributions in DML systems primarily focuses on protecting models from being exploited by workers who contribute incorrect or misleading data. However, less… More >

Youlin Ji, Bo Yin^*, Ke Gu

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 4205-4223, 2024, DOI:10.32604/cmc.2024.049086 - 26 March 2024

Abstract With its untameable and traceable properties, blockchain technology has been widely used in the field of data sharing. How to preserve individual privacy while enabling efficient data queries is one of the primary issues with secure data sharing. In this paper, we study verifiable keyword frequency (KF) queries with local differential privacy in blockchain. Both the numerical and the keyword attributes are present in data objects; the latter are sensitive and require privacy protection. However, prior studies in blockchain have the problem of trilemma in privacy protection and are unable to handle KF queries. We… More >