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  • Open Access


    An Efficient Three-Party Authenticated Key Exchange Procedure Using Chebyshev Chaotic Maps with Client Anonymity

    Akshaykumar Meshram1,2, Monia Hadj Alouane-Turki3, N. M. Wazalwar2, Chandrashekhar Meshram4,*

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5337-5353, 2023, DOI:10.32604/cmc.2023.037324

    Abstract Internet of Things (IoT) applications can be found in various industry areas, including critical infrastructure and healthcare, and IoT is one of several technological developments. As a result, tens of billions or possibly hundreds of billions of devices will be linked together. These smart devices will be able to gather data, process it, and even come to decisions on their own. Security is the most essential thing in these situations. In IoT infrastructure, authenticated key exchange systems are crucial for preserving client and data privacy and guaranteeing the security of data-in-transit (e.g., via client identification and provision of secure communication).… More >

  • Open Access


    A Client Selection Method Based on Loss Function Optimization for Federated Learning

    Yan Zeng1,2,3, Siyuan Teng1, Tian Xiang4,*, Jilin Zhang1,2,3, Yuankai Mu5, Yongjian Ren1,2,3,*, Jian Wan1,2,3

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 1047-1064, 2023, DOI:10.32604/cmes.2023.027226

    Abstract Federated learning is a distributed machine learning method that can solve the increasingly serious problem of data islands and user data privacy, as it allows training data to be kept locally and not shared with other users. It trains a global model by aggregating locally-computed models of clients rather than their raw data. However, the divergence of local models caused by data heterogeneity of different clients may lead to slow convergence of the global model. For this problem, we focus on the client selection with federated learning, which can affect the convergence performance of the global model with the selected… More > Graphic Abstract

    A Client Selection Method Based on Loss Function Optimization for Federated Learning

  • Open Access


    Early DDoS Detection and Prevention with Traced-Back Blocking in SDN Environment

    Sriramulu Bojjagani1, D. R. Denslin Brabin2,*, K. Saravanan2

    Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 805-819, 2022, DOI:10.32604/iasc.2022.023771

    Abstract The flow of information is a valuable asset for every company and its consumers, and Distributed Denial-of-Service (DDoS) assaults pose a substantial danger to this flow. If we do not secure security, hackers may steal information flowing across a network, posing a danger to a business and society. As a result, the most effective ways are necessary to deal with the dangers. A DDoS attack is a well-known network infrastructure assault that prevents servers from servicing genuine customers. It is necessary to identify and block a DDoS assault before it reaches the server in order to avoid being refused services.… More >

  • Open Access


    Artificial Intelligence Based Language Translation Platform

    Manjur Kolhar*, Abdalla Alameen

    Intelligent Automation & Soft Computing, Vol.28, No.1, pp. 1-9, 2021, DOI:10.32604/iasc.2021.014995

    Abstract The use of computer-based technologies by non-native Arabic-speaking teachers for teaching native Arabic-speaking students can result in higher learner engagement. In this study, a machine translation (MT) system is developed as a learning technology. The proposed system can be linked to a digital podium and projector to reduce multitasking. A total of 25 students from Prince Sattam Bin Abdulaziz University, Saudi Arabia participated in our experiment and survey related to the use of the proposed technology-enhanced MT system. An important reason for using this framework is to exploit the high service bandwidth (up to several bandwidths) made available for interactive… More >

  • Open Access


    Lightweight Mobile Clients Privacy Protection Using Trusted Execution Environments for Blockchain

    Jieren Cheng1, Jun Li2, *, Naixue Xiong3, Meizhu Chen2, Hao Guo2, Xinzhi Yao2

    CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2247-2262, 2020, DOI:10.32604/cmc.2020.011668

    Abstract Nowadays, as lightweight mobile clients become more powerful and widely used, more and more information is stored on lightweight mobile clients, user sensitive data privacy protection has become an urgent concern and problem to be solved. There has been a corresponding rise of security solutions proposed by researchers, however, the current security mechanisms on lightweight mobile clients are proven to be fragile. Due to the fact that this research field is immature and still unexplored in-depth, with this paper, we aim to provide a structured and comprehensive study on privacy protection using trusted execution environment (TEE) for lightweight mobile clients.… More >

  • Open Access


    Integration of Peridynamic Theory and OpenSees for Solving Problems in Civil Engineering

    Quan Gu1, Lei Wang1, Surong Huang2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.120, No.3, pp. 471-489, 2019, DOI:10.32604/cmes.2019.05757

    Abstract Peridynamics (PD) is a powerful method to simulate the discontinuous problems in civil engineering. However, it may take a lot of effort to implement the material constitutive models into PD program for solving a broad range of problems. OpenSees is an open source software which includes a versatile material library and has been widely used by researchers and engineers in civil engineering. In this context, the paper presents a simple but effective approach to integrate PD with OpenSees by using a Client-Server (CS) software integration technique, such that the existing material constitutive models in OpenSees can be directly used by… More >

  • Open Access


    Enabling Comparable Search Over Encrypted Data for IoT with Privacy-Preserving

    Lei Xu1, Chungen Xu1,*, Zhongyi Liu1, Yunling Wang2,3, Jianfeng Wang2,3

    CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 675-690, 2019, DOI:10.32604/cmc.2019.05276

    Abstract With the rapid development of cloud computing and Internet of Things (IoT) technology, massive data raises and shuttles on the network every day. To ensure the confidentiality and utilization of these data, industries and companies users encrypt their data and store them in an outsourced party. However, simple adoption of encryption scheme makes the original lose its flexibility and utilization. To address these problems, the searchable encryption scheme is proposed. Different from traditional encrypted data search scheme, this paper focuses on providing a solution to search the data from one or more IoT device by comparing their underlying numerical values.… More >

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