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  • Open Access

    ARTICLE

    A Privacy-Preserving Convolutional Neural Network Inference Framework for AIoT Applications

    Haoran Wang1, Shuhong Yang2, Kuan Shao2, Tao Xiao2, Zhenyong Zhang2,*

    CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-18, 2026, DOI:10.32604/cmc.2025.069404 - 10 November 2025

    Abstract With the rapid development of the Artificial Intelligence of Things (AIoT), convolutional neural networks (CNNs) have demonstrated potential and remarkable performance in AIoT applications due to their excellent performance in various inference tasks. However, the users have concerns about privacy leakage for the use of AI and the performance and efficiency of computing on resource-constrained IoT edge devices. Therefore, this paper proposes an efficient privacy-preserving CNN framework (i.e., EPPA) based on the Fully Homomorphic Encryption (FHE) scheme for AIoT application scenarios. In the plaintext domain, we verify schemes with different activation structures to determine the… More >

  • Open Access

    ARTICLE

    A Novel Malware Detection Framework for Internet of Things Applications

    Muhammad Adil1,*, Mona M. Jamjoom2, Zahid Ullah3

    CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 4363-4380, 2025, DOI:10.32604/cmc.2025.066551 - 30 July 2025

    Abstract In today’s digital world, the Internet of Things (IoT) plays an important role in both local and global economies due to its widespread adoption in different applications. This technology has the potential to offer several advantages over conventional technologies in the near future. However, the potential growth of this technology also attracts attention from hackers, which introduces new challenges for the research community that range from hardware and software security to user privacy and authentication. Therefore, we focus on a particular security concern that is associated with malware detection. The literature presents many countermeasures, but… More >

  • Open Access

    REVIEW

    A Detailed Review of Current AI Solutions for Enhancing Security in Internet of Things Applications

    Arshiya Sajid Ansari1,*, Ghadir Altuwaijri2, Fahad Alodhyani1, Moulay Ibrahim El-Khalil Ghembaza3, Shahabas Manakunnath Devasam Paramb3, Mohammad Sajid Mohammadi3

    CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 3713-3752, 2025, DOI:10.32604/cmc.2025.064027 - 19 May 2025

    Abstract IoT has emerged as a game-changing technology that connects numerous gadgets to networks for communication, processing, and real-time monitoring across diverse applications. Due to their heterogeneous nature and constrained resources, as well as the growing trend of using smart gadgets, there are privacy and security issues that are not adequately managed by conventional security measures. This review offers a thorough analysis of contemporary AI solutions designed to enhance security within IoT ecosystems. The intersection of AI technologies, including ML, and blockchain, with IoT privacy and security is systematically examined, focusing on their efficacy in addressing… More >

  • Open Access

    ARTICLE

    Reliable Task Offloading for 6G-Based IoT Applications

    Usman Mahmood Malik1, Muhammad Awais Javed2, Ahmad Naseem Alvi2, Mohammed Alkhathami3,*

    CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 2255-2274, 2025, DOI:10.32604/cmc.2025.061254 - 17 February 2025

    Abstract Fog computing is a key enabling technology of 6G systems as it provides quick and reliable computing, and data storage services which are required for several 6G applications. Artificial Intelligence (AI) algorithms will be an integral part of 6G systems and efficient task offloading techniques using fog computing will improve their performance and reliability. In this paper, the focus is on the scenario of Partial Offloading of a Task to Multiple Helpers (POMH) in which larger tasks are divided into smaller subtasks and processed in parallel, hence expediting task completion. However, using POMH presents challenges… More >

  • Open Access

    ARTICLE

    Enabling Efficient Data Transmission in Wireless Sensor Networks-Based IoT Applications

    Ibraheem Al-Hejri1, Farag Azzedin1,*, Sultan Almuhammadi1, Naeem Firdous Syed2

    CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 4197-4218, 2024, DOI:10.32604/cmc.2024.047117 - 20 June 2024

    Abstract The use of the Internet of Things (IoT) is expanding at an unprecedented scale in many critical applications due to the ability to interconnect and utilize a plethora of wide range of devices. In critical infrastructure domains like oil and gas supply, intelligent transportation, power grids, and autonomous agriculture, it is essential to guarantee the confidentiality, integrity, and authenticity of data collected and exchanged. However, the limited resources coupled with the heterogeneity of IoT devices make it inefficient or sometimes infeasible to achieve secure data transmission using traditional cryptographic techniques. Consequently, designing a lightweight secure More >

  • Open Access

    ARTICLE

    Multi-Layer Fog-Cloud Architecture for Optimizing the Placement of IoT Applications in Smart Cities

    Mohammad Aldossary*

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 633-649, 2023, DOI:10.32604/cmc.2023.035414 - 06 February 2023

    Abstract In the smart city paradigm, the deployment of Internet of Things (IoT) services and solutions requires extensive communication and computing resources to place and process IoT applications in real time, which consumes a lot of energy and increases operational costs. Usually, IoT applications are placed in the cloud to provide high-quality services and scalable resources. However, the existing cloud-based approach should consider the above constraints to efficiently place and process IoT applications. In this paper, an efficient optimization approach for placing IoT applications in a multi-layer fog-cloud environment is proposed using a mathematical model (Mixed-Integer… More >

  • Open Access

    ARTICLE

    Digital Twin-Based Automated Fault Diagnosis in Industrial IoT Applications

    Samah Alshathri1, Ezz El-Din Hemdan2, Walid El-Shafai3,4,*, Amged Sayed5,6

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 183-196, 2023, DOI:10.32604/cmc.2023.034048 - 06 February 2023

    Abstract In recent years, Digital Twin (DT) has gained significant interest from academia and industry due to the advanced in information technology, communication systems, Artificial Intelligence (AI), Cloud Computing (CC), and Industrial Internet of Things (IIoT). The main concept of the DT is to provide a comprehensive tangible, and operational explanation of any element, asset, or system. However, it is an extremely dynamic taxonomy developing in complexity during the life cycle that produces a massive amount of engendered data and information. Likewise, with the development of AI, digital twins can be redefined and could be a… More >

  • Open Access

    ARTICLE

    An Anti-Physical Attack Scheme of ARX Lightweight Algorithms for IoT Applications

    Qiang Zhi1, Xiang Jiang1, Hangying Zhang2, Zhengshu Zhou3, Jianguo Ren1, Tong Huang4,*

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 389-402, 2023, DOI:10.32604/csse.2023.035576 - 20 January 2023

    Abstract The lightweight encryption algorithm based on Add-Rotation-XOR (ARX) operation has attracted much attention due to its high software affinity and fast operation speed. However, lacking an effective defense scheme for physical attacks limits the applications of the ARX algorithm. The critical challenge is how to weaken the direct dependence between the physical information and the secret key of the algorithm at a low cost. This study attempts to explore how to improve its physical security in practical application scenarios by analyzing the masking countermeasures of ARX algorithms and the leakage causes. Firstly, we specify a More >

  • Open Access

    ARTICLE

    A Blockchain-Based Architecture for Securing Industrial IoTs Data in Electric Smart Grid

    Samir M. Umran1,2, Songfeng Lu1,3, Zaid Ameen Abduljabbar1,4, Xueming Tang1,*

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5389-5416, 2023, DOI:10.32604/cmc.2023.034331 - 28 December 2022

    Abstract There are numerous internet-connected devices attached to the industrial process through recent communication technologies, which enable machine-to-machine communication and the sharing of sensitive data through a new technology called the industrial internet of things (IIoTs). Most of the suggested security mechanisms are vulnerable to several cybersecurity threats due to their reliance on cloud-based services, external trusted authorities, and centralized architectures; they have high computation and communication costs, low performance, and are exposed to a single authority of failure and bottleneck. Blockchain technology (BC) is widely adopted in the industrial sector for its valuable features in… More >

  • Open Access

    ARTICLE

    LSTM Based Spectrum Prediction for Real-Time Spectrum Access for IoT Applications

    R. Nandakumar1, Vijayakumar Ponnusamy2,*, Aman Kumar Mishra2

    Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 2805-2819, 2023, DOI:10.32604/iasc.2023.028645 - 17 August 2022

    Abstract In the Internet of Things (IoT) scenario, many devices will communicate in the presence of the cellular network; the chances of availability of spectrum will be very scary given the presence of large numbers of mobile users and large amounts of applications. Spectrum prediction is very encouraging for high traffic next-generation wireless networks, where devices/machines which are part of the Cognitive Radio Network (CRN) can predict the spectrum state prior to transmission to save their limited energy by avoiding unnecessarily sensing radio spectrum. Long short-term memory (LSTM) is employed to simultaneously predict the Radio Spectrum More >

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