Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (36)
  • Open Access

    ARTICLE

    A Fair and Trusted Trading Scheme for Medical Data Based on Smart Contracts

    Xiaohui Yang, Kun Zhang*

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

    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 >

  • Open Access

    ARTICLE

    An Energy Trading Method Based on Alliance Blockchain and Multi-Signature

    Hongliang Tian, Jiaming Wang*

    CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 1611-1629, 2024, DOI:10.32604/cmc.2023.046698

    Abstract Blockchain, known for its secure encrypted ledger, has garnered attention in financial and data transfer realms, including the field of energy trading. However, the decentralized nature and identity anonymity of user nodes raise uncertainties in energy transactions. The broadcast consensus authentication slows transaction speeds, and frequent single-point transactions in multi-node settings pose key exposure risks without protective measures during user signing. To address these, an alliance blockchain scheme is proposed, reducing the resource-intensive identity verification among nodes. It integrates multi-signature functionality to fortify user resources and transaction security. A novel multi-signature process within this framework… More >

  • Open Access

    ARTICLE

    A Novel High-Efficiency Transaction Verification Scheme for Blockchain Systems

    Jingyu Zhang1,2, Pian Zhou1, Jin Wang1, Osama Alfarraj3, Saurabh Singh4, Min Zhu5,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1613-1633, 2024, DOI:10.32604/cmes.2023.044418

    Abstract Blockchain can realize the reliable storage of a large amount of data that is chronologically related and verifiable within the system. This technology has been widely used and has developed rapidly in big data systems across various fields. An increasing number of users are participating in application systems that use blockchain as their underlying architecture. As the number of transactions and the capital involved in blockchain grow, ensuring information security becomes imperative. Addressing the verification of transactional information security and privacy has emerged as a critical challenge. Blockchain-based verification methods can effectively eliminate the need… More >

  • Open Access

    ARTICLE

    Inter-Provincial Transaction Model in Two-Level Electricity Market Considering Carbon Emission and Consumption Responsibility Weights

    Chunlei Jiao1, Hongyan Hao2, Ming Li1,*, Rifucairen Fu1, Yichun Liu3, Shunfu Lin3, Ronghui Liu3

    Energy Engineering, Vol.120, No.10, pp. 2393-2416, 2023, DOI:10.32604/ee.2023.028574

    Abstract In the context of the joint operation of China’s intra-provincial markets and inter-provincial trading, how to meet the load demand and energy consumption using inter-provincial renewable energy trading is a key problem. The combined operation of intra-provincial and inter-provincial markets provides a new way for provincial power companies to optimize and clear the intra-provincial power market, complete the intra-provincial consumption responsibility weight index, and consume renewable energy across provinces and regions. This paper combines power generation and consumption within the province, uses inter-provincial renewable energy trading to meet the load demand within the province and… More >

  • Open Access

    REVIEW

    Blockchain-Enabled Cybersecurity Provision for Scalable Heterogeneous Network: A Comprehensive Survey

    Md. Shohidul Islam1,*, Md. Arafatur Rahman2, Mohamed Ariff Bin Ameedeen1, Husnul Ajra1, Zahian Binti Ismail1, Jasni Mohamad Zain3

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 43-123, 2024, DOI:10.32604/cmes.2023.028687

    Abstract Blockchain-enabled cybersecurity system to ensure and strengthen decentralized digital transaction is gradually gaining popularity in the digital era for various areas like finance, transportation, healthcare, education, and supply chain management. Blockchain interactions in the heterogeneous network have fascinated more attention due to the authentication of their digital application exchanges. However, the exponential development of storage space capabilities across the blockchain-based heterogeneous network has become an important issue in preventing blockchain distribution and the extension of blockchain nodes. There is the biggest challenge of data integrity and scalability, including significant computing complexity and inapplicable latency on… More > Graphic Abstract

    Blockchain-Enabled Cybersecurity Provision for Scalable Heterogeneous Network: A Comprehensive Survey

  • Open Access

    ARTICLE

    Intelligent Financial Fraud Detection Using Artificial Bee Colony Optimization Based Recurrent Neural Network

    T. Karthikeyan1,*, M. Govindarajan1, V. Vijayakumar2

    Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 1483-1498, 2023, DOI:10.32604/iasc.2023.037606

    Abstract Frauds don’t follow any recurring patterns. They require the use of unsupervised learning since their behaviour is continually changing. Fraudsters have access to the most recent technology, which gives them the ability to defraud people through online transactions. Fraudsters make assumptions about consumers’ routine behaviour, and fraud develops swiftly. Unsupervised learning must be used by fraud detection systems to recognize online payments since some fraudsters start out using online channels before moving on to other techniques. Building a deep convolutional neural network model to identify anomalies from conventional competitive swarm optimization patterns with a focus… More >

  • Open Access

    ARTICLE

    An Interoperability Cross-Block Chain Framework for Secure Transactions in IoT

    N. Anand Kumar1,*, A. Grace Selvarani2, P. Vivekanandan3

    Computer Systems Science and Engineering, Vol.47, No.1, pp. 1077-1090, 2023, DOI:10.32604/csse.2023.034115

    Abstract The purpose of this research is to deal with effective block chain framework for secure transactions. The rate of effective data transactions and the interoperability of the ledger are the two major obstacles involved in Blockchain and to tackle this issue, Cross-Chain based Transaction (CCT) is introduced. Traditional industries have been restructured by the introduction of Internet of Things (IoT) to become smart industries through the feature of data-driven decision-making. Still, there are a few limitations, like decentralization, security vulnerabilities, poor interoperability, as well as privacy concerns in IoTs. To overcome this limitation, Blockchain has… More >

  • Open Access

    ARTICLE

    Hybrid Graph Partitioning with OLB Approach in Distributed Transactions

    Rajesh Bharati*, Vahida Attar

    Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 763-775, 2023, DOI:10.32604/iasc.2023.035503

    Abstract Online Transaction Processing (OLTP) gets support from data partitioning to achieve better performance and scalability. The primary objective of database and application developers is to provide scalable and reliable database systems. This research presents a novel method for data partitioning and load balancing for scalable transactions. Data is efficiently partitioned using the hybrid graph partitioning method. Optimized load balancing (OLB) approach is applied to calculate the weight factor, average workload, and partition efficiency. The presented approach is appropriate for various online data transaction applications. The quality of the proposed approach is examined using OLTP database More >

  • Open Access

    ARTICLE

    Lightweight Storage Framework for Blockchain-Enabled Internet of Things Under Cloud Computing

    Xinyi Qing1,3, Baopeng Ye2, Yuanquan Shi1,3, Tao Li4,*, Yuling Chen4, Lei Liu1

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3607-3624, 2023, DOI:10.32604/cmc.2023.037532

    Abstract Due to its decentralized, tamper-proof, and trust-free characteristics, blockchain is used in the Internet of Things (IoT) to guarantee the reliability of data. However, some technical flaws in blockchain itself prevent the development of these applications, such as the issue with linearly growing storage capacity of blockchain systems. On the other hand, there is a lack of storage resources for sensor devices in IoT, and numerous sensor devices will generate massive data at ultra-high speed, which makes the storage problem of the IoT enabled by blockchain more prominent. There are various solutions to reduce the… More >

  • Open Access

    ARTICLE

    Smart Fraud Detection in E-Transactions Using Synthetic Minority Oversampling and Binary Harris Hawks Optimization

    Chandana Gouri Tekkali, Karthika Natarajan*

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3171-3187, 2023, DOI:10.32604/cmc.2023.036865

    Abstract Fraud Transactions are haunting the economy of many individuals with several factors across the globe. This research focuses on developing a mechanism by integrating various optimized machine-learning algorithms to ensure the security and integrity of digital transactions. This research proposes a novel methodology through three stages. Firstly, Synthetic Minority Oversampling Technique (SMOTE) is applied to get balanced data. Secondly, SMOTE is fed to the nature-inspired Meta Heuristic (MH) algorithm, namely Binary Harris Hawks Optimization (BinHHO), Binary Aquila Optimization (BAO), and Binary Grey Wolf Optimization (BGWO), for feature selection. BinHHO has performed well when compared with More >

Displaying 1-10 on page 1 of 36. Per Page