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  • Open Access


    Blockchain-Based Cognitive Computing Model for Data Security on a Cloud Platform

    Xiangmin Guo1,2, Guangjun Liang1,2,*, Jiayin Liu1,2, Xianyi Chen3,*

    CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3305-3323, 2023, DOI:10.32604/cmc.2023.044529

    Abstract Cloud storage is widely used by large companies to store vast amounts of data and files, offering flexibility, financial savings, and security. However, information shoplifting poses significant threats, potentially leading to poor performance and privacy breaches. Blockchain-based cognitive computing can help protect and maintain information security and privacy in cloud platforms, ensuring businesses can focus on business development. To ensure data security in cloud platforms, this research proposed a blockchain-based Hybridized Data Driven Cognitive Computing (HD2C) model. However, the proposed HD2C framework addresses breaches of the privacy information of mixed participants of the Internet of… More >

  • Open Access


    A Novel Machine Learning–Based Hand Gesture Recognition Using HCI on IoT Assisted Cloud Platform

    Saurabh Adhikari1, Tushar Kanti Gangopadhayay1, Souvik Pal2,3, D. Akila4, Mamoona Humayun5, Majed Alfayad6, N. Z. Jhanjhi7,*

    Computer Systems Science and Engineering, Vol.46, No.2, pp. 2123-2140, 2023, DOI:10.32604/csse.2023.034431

    Abstract Machine learning is a technique for analyzing data that aids the construction of mathematical models. Because of the growth of the Internet of Things (IoT) and wearable sensor devices, gesture interfaces are becoming a more natural and expedient human-machine interaction method. This type of artificial intelligence that requires minimal or no direct human intervention in decision-making is predicated on the ability of intelligent systems to self-train and detect patterns. The rise of touch-free applications and the number of deaf people have increased the significance of hand gesture recognition. Potential applications of hand gesture recognition research… More >

  • Open Access


    Dynamic Data Optimization in IoT-Assisted Sensor Networks on Cloud Platform

    Nguyen A. Tuan1, D. Akila2, Souvik Pal3, Bikramjit Sarkar4, Thien Khai Tran1, G. Mothilal Nehru2, Dac-Nhuong Le5,6,*

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1357-1372, 2022, DOI:10.32604/cmc.2022.024096

    Abstract This article presents a new scheme for dynamic data optimization in IoT (Internet of Things)-assisted sensor networks. The various components of IoT assisted cloud platform are discussed. In addition, a new architecture for IoT assisted sensor networks is presented. Further, a model for data optimization in IoT assisted sensor networks is proposed. A novel Membership inducing Dynamic Data Optimization Membership inducing Dynamic Data Optimization (MIDDO) algorithm for IoT assisted sensor network is proposed in this research. The proposed algorithm considers every node data and utilized membership function for the optimized data allocation. The proposed framework More >

  • Open Access


    Design and Implementation of Open Source Online Evaluation System Based on Cloud Platform

    Zuwei Tian*, Shubo Tian, Tuo Wang, Zhen Gong, Zhenqin Jiang

    Journal on Big Data, Vol.2, No.3, pp. 117-123, 2020, DOI:10.32604/jbd.2020.011420

    Abstract In order to provide a good practice platform for the program design contestants and algorithm enthusiasts, this paper designs and implements a programming online evaluation system based on cloud platform, which is a web system that can return the test results of the program source codes submitted by users in real time. It realizes the automatic evaluation of the program design training questions. The system is implemented by the way of front-end and backend separation and modular programming. The front-end of the web is implemented by Vue framework, the back-end is implemented by Django framework. More >

  • Open Access


    A New Rockburst Experiment Data Compression Storage Algorithm Based on Big Data Technology

    Yu Zhang1,2, Yan-Ge Wang1, Yan-Ping Bai3, Yong-Zhen Li1,4, Zhao-Yong Lv5, Hong-Wei Ding6

    Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 561-572, 2019, DOI:10.31209/2019.100000111

    Abstract Rockburst phenomenon is a kind of phenomenon that the rock is out and ejected because the mineral was dug out, and the original force balance was destroyed in the process of mineral exploitation. From 2007, GeoLab (abbreviation of State Key Laboratory in China for GeoMechanics and Deep Underground Engineering) had made a series of important achievements in rockburst. Up to now, GeoLab’s rockburst experiment data is reached 800T, and these data may occupy about 2PB hard disk space after analyzed. At this ratio, GeoLab need to buy a new hard disk to save all these… More >

  • Open Access


    Fine-Grained Binary Analysis Method for Privacy Leakage Detection on the Cloud Platform

    Jiaye Pan1, Yi Zhuang1, *, Xinwen Hu1, 2, Wenbing Zhao3

    CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 607-622, 2020, DOI:10.32604/cmc.2020.09853

    Abstract Nowadays cloud architecture is widely applied on the internet. New malware aiming at the privacy data stealing or crypto currency mining is threatening the security of cloud platforms. In view of the problems with existing application behavior monitoring methods such as coarse-grained analysis, high performance overhead and lack of applicability, this paper proposes a new fine-grained binary program monitoring and analysis method based on multiple system level components, which is used to detect the possible privacy leakage of applications installed on cloud platforms. It can be used online in cloud platform environments for fine-grained automated… More >

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