Shuai Zhao, Zhiwei Zhang^*, Junkai Wang, Ye Yuan, Guoren Wang

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.073315 - 12 January 2026

Abstract With the development of sharded blockchains, high cross-shard rates and load imbalance have emerged as major challenges. Account partitioning based on hashing and real-time load faces the issue of high cross-shard rates. Account partitioning based on historical transaction graphs is effective in reducing cross-shard rates but suffers from load imbalance and limited adaptability to dynamic workloads. Meanwhile, because of the coupling between consensus and execution, a target shard must receive both the partitioned transactions and the partitioned accounts before initiating consensus and execution. However, we observe that transaction partitioning and subsequent consensus do not require… More >

Naif Almusallam^1,*, Junaid Qayyum^2,3

CMC-Computers, Materials & Continua, Vol.85, No.2, pp. 3653-3687, 2025, DOI:10.32604/cmc.2025.067220 - 23 September 2025

Abstract This paper proposes a novel hybrid fraud detection framework that integrates multi-stage feature selection, unsupervised clustering, and ensemble learning to improve classification performance in financial transaction monitoring systems. The framework is structured into three core layers: (1) feature selection using Recursive Feature Elimination (RFE), Principal Component Analysis (PCA), and Mutual Information (MI) to reduce dimensionality and enhance input relevance; (2) anomaly detection through unsupervised clustering using K-Means, Density-Based Spatial Clustering (DBSCAN), and Hierarchical Clustering to flag suspicious patterns in unlabeled data; and (3) final classification using a voting-based hybrid ensemble of Support Vector Machine (SVM),… More >

Amal Al-Rasheed¹, Hashim Ali^2,*, Rahim Khan^2,*, Aamir Saeed³

CMC-Computers, Materials & Continua, Vol.85, No.2, pp. 3419-3436, 2025, DOI:10.32604/cmc.2025.065156 - 23 September 2025

Abstract In the domain of Electronic Medical Records (EMRs), emerging technologies are crucial to addressing longstanding concerns surrounding transaction security and patient privacy. This paper explores the integration of smart contracts and blockchain technology as a robust framework for securing sensitive healthcare data. By leveraging the decentralized and immutable nature of blockchain, the proposed approach ensures transparency, integrity, and traceability of EMR transactions, effectively mitigating risks of unauthorized access and data tampering. Smart contracts further enhance this framework by enabling the automation and enforcement of secure transactions, eliminating reliance on intermediaries and reducing the potential for… More >

Jiao Li, Xiaoyu Song^*

CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 5239-5254, 2025, DOI:10.32604/cmc.2025.065504 - 30 July 2025

Abstract The long transaction latency and low throughput of blockchain are the key challenges affecting the large-scale adoption of blockchain technology. Sharding technology is a primary solution by divides the blockchain network into multiple independent shards for parallel transaction processing. However, most existing random or modular schemes fail to consider the transactional relationships between accounts, which leads to a high proportion of cross-shard transactions, thereby increasing the communication overhead and transaction confirmation latency between shards. To solve this problem, this paper proposes a blockchain sharding algorithm based on account degree and frequency (DFSA). The algorithm takes… More >

Jiling Wan, Lifeng Cao^*, Jinlong Bai, Jinhui Li, Xuehui Du

CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 4775-4794, 2025, DOI:10.32604/cmc.2025.061964 - 19 May 2025

Abstract Blockchain platforms with the unique characteristics of anonymity, decentralization, and transparency of their transactions, which are faced with abnormal activities such as money laundering, phishing scams, and fraudulent behavior, posing a serious threat to account asset security. For these potential security risks, this paper proposes a hybrid neural network detection method (HNND) that learns multiple types of account features and enhances fusion information among them to effectively detect abnormal transaction behaviors in the blockchain. In HNND, the Temporal Transaction Graph Attention Network (T2GAT) is first designed to learn biased aggregation representation of multi-attribute transactions among More >

Xingxu Zhu¹, Guiqing Zhao¹, Gangui Yan¹, Junhui Li^1,*, Hongda Dong², Chenggang Li²

Energy Engineering, Vol.122, No.5, pp. 1645-1668, 2025, DOI:10.32604/ee.2025.063192 - 25 April 2025

Abstract The participation of wind farms in the former energy market faces challenges such as power fluctuations and energy storage construction costs. To this end, this paper proposes a joint energy storage operation scheme for multiple wind farms based on a leasing model, which assists wind farms in bidding for participation in the former energy market through leasing services, thereby enhancing energy storage efficiency and maximizing economic benefits. In this paper, based on the Weibull probability distribution to portray the uncertainty of wind power, and considering the lifetime capacity loss caused by charging and discharging of… More > Graphic Abstract

Hongliang Tian, Zuoqing Li^*

CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 3983-4002, 2025, DOI:10.32604/cmc.2025.059103 - 06 March 2025

Abstract Low data encryption efficiency and inadequate security are two issues with the current blockchain cross-chain transaction protection schemes. To address these issues, a blockchain cross-chain transaction protection scheme based on Fully Homomorphic Encryption (FHE) is proposed. In the proposed scheme, the functional relationship is established by Box-Muller, Discrete Gaussian Distribution Function (DGDF) and Uniform Random Distribution Function (URDF) are used to improve the security and efficiency of key generation. Subsequently, the data preprocessing function is introduced to perform cleaning, deduplication, and normalization operations on the transaction data of multi-key signature, and it is classified into… More >

Jawad Ahmad Ansari¹, Mohamad Khairi Ishak^2,*, Khalid Ammar²

CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 2311-2330, 2025, DOI:10.32604/cmc.2025.057848 - 17 February 2025

Abstract Cyber-Physical System (CPS) devices are increasing exponentially. Lacking confidentiality creates a vulnerable network. Thus, demanding the overall system with the latest and robust solutions for the defence mechanisms with low computation cost, increased integrity, and surveillance. The proposal of a mechanism that utilizes the features of authenticity measures using the Destination Sequence Distance Vector (DSDV) routing protocol which applies to the multi-WSN (Wireless Sensor Network) of IoT devices in CPS which is developed for the Device-to-Device (D2D) authentication developed from the local-chain and public chain respectively combined with the Software Defined Networking (SDN) control and… More >

Jiawei Qin^1,2, Hua Zhang^1,*, Hanbing Yan², Tian Zhu², Song Hu¹, Dingyu Yan²

Intelligent Automation & Soft Computing, Vol.39, No.3, pp. 527-544, 2024, DOI:10.32604/iasc.2024.047509 - 11 July 2024

Abstract By the analysis of vulnerabilities of Android native system services, we find that some vulnerabilities are caused by inconsistent data transmission and inconsistent data processing logic between client and server. The existing research cannot find the above two types of vulnerabilities and the test cases of them face the problem of low coverage. In this paper, we propose an extraction method of test cases based on the native system services of the client and design a case construction method that supports multi-parameter mutation based on genetic algorithm and priority strategy. Based on the above method, More >

Xiaohui Yang, Kun Zhang^*

CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 1843-1859, 2024, DOI:10.32604/cmc.2023.047660 - 27 February 2024

Abstract Data is regarded as a valuable asset, and sharing data is a prerequisite for fully exploiting the value of data. However, the current medical data sharing scheme lacks a fair incentive mechanism, and the authenticity of data cannot be guaranteed, resulting in low enthusiasm of participants. A fair and trusted medical data trading scheme based on smart contracts is proposed, which aims to encourage participants to be honest and improve their enthusiasm for participation. The scheme uses zero-knowledge range proof for trusted verification, verifies the authenticity of the patient’s data and the specific attributes of… More >