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  • Open Access

    ARTICLE

    Software Defined Range-Proof Authentication Mechanism for Untraceable Digital ID

    So-Eun Jeon1, Yeon-Ji Lee2, Il-Gu Lee1,2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.3, pp. 3213-3228, 2025, DOI:10.32604/cmes.2025.062082 - 03 March 2025

    Abstract The Internet of Things (IoT) is extensively applied across various industrial domains, such as smart homes, factories, and intelligent transportation, becoming integral to daily life. Establishing robust policies for managing and governing IoT devices is imperative. Secure authentication for IoT devices in resource-constrained environments remains challenging due to the limitations of conventional complex protocols. Prior methodologies enhanced mutual authentication through key exchange protocols or complex operations, which are impractical for lightweight devices. To address this, our study introduces the privacy-preserving software-defined range proof (SDRP) model, which achieves secure authentication with low complexity. SDRP minimizes the More >

  • Open Access

    ARTICLE

    ANNDRA-IoT: A Deep Learning Approach for Optimal Resource Allocation in Internet of Things Environments

    Abdullah M. Alqahtani1,*, Kamran Ahmad Awan2, Abdulaziz Almaleh3, Osama Aletri4

    CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.3, pp. 3155-3179, 2025, DOI:10.32604/cmes.2025.061472 - 03 March 2025

    Abstract Efficient resource management within Internet of Things (IoT) environments remains a pressing challenge due to the increasing number of devices and their diverse functionalities. This study introduces a neural network-based model that uses Long-Short-Term Memory (LSTM) to optimize resource allocation under dynamically changing conditions. Designed to monitor the workload on individual IoT nodes, the model incorporates long-term data dependencies, enabling adaptive resource distribution in real time. The training process utilizes Min-Max normalization and grid search for hyperparameter tuning, ensuring high resource utilization and consistent performance. The simulation results demonstrate the effectiveness of the proposed method, More >

  • Open Access

    ARTICLE

    Quantum Inspired Adaptive Resource Management Algorithm for Scalable and Energy Efficient Fog Computing in Internet of Things (IoT)

    Sonia Khan1, Naqash Younas2, Musaed Alhussein3, Wahib Jamal Khan2, Muhammad Shahid Anwar4,*, Khursheed Aurangzeb3

    CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.3, pp. 2641-2660, 2025, DOI:10.32604/cmes.2025.060973 - 03 March 2025

    Abstract Effective resource management in the Internet of Things and fog computing is essential for efficient and scalable networks. However, existing methods often fail in dynamic and high-demand environments, leading to resource bottlenecks and increased energy consumption. This study aims to address these limitations by proposing the Quantum Inspired Adaptive Resource Management (QIARM) model, which introduces novel algorithms inspired by quantum principles for enhanced resource allocation. QIARM employs a quantum superposition-inspired technique for multi-state resource representation and an adaptive learning component to adjust resources in real time dynamically. In addition, an energy-aware scheduling module minimizes power More >

  • Open Access

    ARTICLE

    HybridEdge: A Lightweight and Secure Hybrid Communication Protocol for the Edge-Enabled Internet of Things

    Amjad Khan1, Rahim Khan1,*, Fahad Alturise2,*, Tamim Alkhalifah3

    CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 3161-3178, 2025, DOI:10.32604/cmc.2025.060372 - 17 February 2025

    Abstract The Internet of Things (IoT) and edge-assisted networking infrastructures are capable of bringing data processing and accessibility services locally at the respective edge rather than at a centralized module. These infrastructures are very effective in providing a fast response to the respective queries of the requesting modules, but their distributed nature has introduced other problems such as security and privacy. To address these problems, various security-assisted communication mechanisms have been developed to safeguard every active module, i.e., devices and edges, from every possible vulnerability in the IoT. However, these methodologies have neglected one of the… More >

  • Open Access

    REVIEW

    Zero Trust Networks: Evolution and Application from Concept to Practice

    Yongjun Ren1, Zhiming Wang1, Pradip Kumar Sharma2, Fayez Alqahtani3, Amr Tolba4, Jin Wang5,*

    CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 1593-1613, 2025, DOI:10.32604/cmc.2025.059170 - 17 February 2025

    Abstract In the context of an increasingly severe cybersecurity landscape and the growing complexity of offensive and defensive techniques, Zero Trust Networks (ZTN) have emerged as a widely recognized technology. Zero Trust not only addresses the shortcomings of traditional perimeter security models but also consistently follows the fundamental principle of “never trust, always verify.” Initially proposed by John Cortez in 2010 and subsequently promoted by Google, the Zero Trust model has become a key approach to addressing the ever-growing security threats in complex network environments. This paper systematically compares the current mainstream cybersecurity models, thoroughly explores More >

  • Open Access

    ARTICLE

    An Efficient Anti-Quantum Blind Signature with Forward Security for Blockchain-Enabled Internet of Medical Things

    Gang Xu1,2,6, Xinyu Fan1, Xiu-Bo Chen2, Xin Liu4, Zongpeng Li5, Yanhui Mao6,7, Kejia Zhang3,*

    CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 2293-2309, 2025, DOI:10.32604/cmc.2024.057882 - 17 February 2025

    Abstract Blockchain-enabled Internet of Medical Things (BIoMT) has attracted significant attention from academia and healthcare organizations. However, the large amount of medical data involved in BIoMT has also raised concerns about data security and personal privacy protection. To alleviate these concerns, blind signature technology has emerged as an effective method to solve blindness and unforgeability. Unfortunately, most existing blind signature schemes suffer from the security risk of key leakage. In addition, traditional blind signature schemes are also vulnerable to quantum computing attacks. Therefore, it remains a crucial and ongoing challenge to explore the construction of key-secure,… More >

  • Open Access

    ARTICLE

    End-To-End Encryption Enabled Lightweight Mutual Authentication Scheme for Resource Constrained IoT Network

    Shafi Ullah1,*, Haidawati Muhammad Nasir2, Kushsairy Kadir3,*, Akbar Khan1, Ahsanullah Memon4, Shanila Azhar1, Ilyas Khan5, Muhammad Ashraf1

    CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 3223-3249, 2025, DOI:10.32604/cmc.2024.054676 - 17 February 2025

    Abstract Machine-to-machine (M2M) communication networks consist of resource-constrained autonomous devices, also known as autonomous Internet of things (IoTs) or machine-type communication devices (MTCDs) which act as a backbone for Industrial IoT, smart cities, and other autonomous systems. Due to the limited computing and memory capacity, these devices cannot maintain strong security if conventional security methods are applied such as heavy encryption. This article proposed a novel lightweight mutual authentication scheme including elliptic curve cryptography (ECC) driven end-to-end encryption through curve25519 such as (i): efficient end-to-end encrypted communication with pre-calculation strategy using curve25519; and (ii): elliptic curve More >

  • Open Access

    ARTICLE

    Internet of Things Software Engineering Model Validation Using Knowledge-Based Semantic Learning

    Mahmood Alsaadi, Mohammed E. Seno*, Mohammed I. Khalaf

    Intelligent Automation & Soft Computing, Vol.40, pp. 29-52, 2025, DOI:10.32604/iasc.2024.060390 - 10 January 2025

    Abstract The agility of Internet of Things (IoT) software engineering is benchmarked based on its systematic insights for wide application support infrastructure developments. Such developments are focused on reducing the interfacing complexity with heterogeneous devices through applications. To handle the interfacing complexity problem, this article introduces a Semantic Interfacing Obscuration Model (SIOM) for IoT software-engineered platforms. The interfacing obscuration between heterogeneous devices and application interfaces from the testing to real-time validations is accounted for in this model. Based on the level of obscuration between the infrastructure hardware to the end-user software, the modifications through device replacement, More >

  • Open Access

    ARTICLE

    Enhancing Vehicle Overtaking System via LoRa-Enabled Vehicular Communication Approach

    Kwang Chee Seng, Siti Fatimah Abdul Razak*, Sumendra Yogarayan

    Computer Systems Science and Engineering, Vol.49, pp. 239-258, 2025, DOI:10.32604/csse.2024.056582 - 10 January 2025

    Abstract Vehicle overtaking poses significant risks and leads to injuries and losses on Malaysia’s roads. In most scenarios, insufficient and untimely information available to drivers for accessing road conditions and their surrounding environment is the primary factor that causes these incidents. To address these issues, a comprehensive system is required to provide real-time assistance to drivers. Building upon our previous research on a LoRa-based lane change decision-aid system, this study proposes an enhanced Vehicle Overtaking System (VOS). This system utilizes long-range (LoRa) communication for reliable real-time data exchange between vehicles (V2V) and the cloud (V2C). By More >

  • Open Access

    ARTICLE

    Energy-Efficient Internet of Things-Based Wireless Sensor Network for Autonomous Data Validation for Environmental Monitoring

    Tabassum Kanwal1, Saif Ur Rehman1,*, Azhar Imran2, Haitham A. Mahmoud3

    Computer Systems Science and Engineering, Vol.49, pp. 185-212, 2025, DOI:10.32604/csse.2024.056535 - 10 January 2025

    Abstract This study presents an energy-efficient Internet of Things (IoT)-based wireless sensor network (WSN) framework for autonomous data validation in remote environmental monitoring. We address two critical challenges in WSNs: ensuring data reliability and optimizing energy consumption. Our novel approach integrates an artificial neural network (ANN)-based multi-fault detection algorithm with an energy-efficient IoT-WSN architecture. The proposed ANN model is designed to simultaneously detect multiple fault types, including spike faults, stuck-at faults, outliers, and out-of-range faults. We collected sensor data at 5-minute intervals over three months, using temperature and humidity sensors. The ANN was trained on 70%… More >

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