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  • Open Access

    ARTICLE

    A Composite Loss-Based Autoencoder for Accurate and Scalable Missing Data Imputation

    Thierry Mugenzi, Cahit Perkgoz*

    CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-21, 2026, DOI:10.32604/cmc.2025.070381 - 10 November 2025

    Abstract Missing data presents a crucial challenge in data analysis, especially in high-dimensional datasets, where missing data often leads to biased conclusions and degraded model performance. In this study, we present a novel autoencoder-based imputation framework that integrates a composite loss function to enhance robustness and precision. The proposed loss combines (i) a guided, masked mean squared error focusing on missing entries; (ii) a noise-aware regularization term to improve resilience against data corruption; and (iii) a variance penalty to encourage expressive yet stable reconstructions. We evaluate the proposed model across four missingness mechanisms, such as Missing… More >

  • Open Access

    ARTICLE

    PhishNet: A Real-Time, Scalable Ensemble Framework for Smishing Attack Detection Using Transformers and LLMs

    Abeer Alhuzali1,*, Qamar Al-Qahtani1, Asmaa Niyazi1, Lama Alshehri1, Fatemah Alharbi2

    CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-19, 2026, DOI:10.32604/cmc.2025.069491 - 10 November 2025

    Abstract The surge in smishing attacks underscores the urgent need for robust, real-time detection systems powered by advanced deep learning models. This paper introduces PhishNet, a novel ensemble learning framework that integrates transformer-based models (RoBERTa) and large language models (LLMs) (GPT-OSS 120B, LLaMA3.3 70B, and Qwen3 32B) to enhance smishing detection performance significantly. To mitigate class imbalance, we apply synthetic data augmentation using T5 and leverage various text preprocessing techniques. Our system employs a dual-layer voting mechanism: weighted majority voting among LLMs and a final ensemble vote to classify messages as ham, spam, or smishing. Experimental More >

  • Open Access

    ARTICLE

    Scalable and Passive Concentrator Photovoltaics Using a Multi-Focal Pyramidal Array: A Multi-Physics Modeling Approach

    Mussad Mohammed Al-Zahrani*, Taher Maatallah

    Frontiers in Heat and Mass Transfer, Vol.23, No.6, pp. 1883-1905, 2025, DOI:10.32604/fhmt.2025.074656 - 31 December 2025

    Abstract Conventional concentrator photovoltaics (CPV) face a persistent trade-off between high efficiency and high cost, driven by expensive multi-junction solar cells and complex active cooling systems. This study presents a computational investigation of a novel Multi-Focal Pyramidal Array (MFPA)-based CPV system designed to overcome this limitation. The MFPA architecture employs a geometrically optimized pyramidal concentrator to distribute concentrated sunlight onto strategically placed, low-cost monocrystalline silicon cells, enabling high efficiency energy capture while passively managing thermal loads. Coupled optical thermal electrical simulations in COMSOL Multiphysics demonstrate a geometric concentration ratio of 120×, with system temperatures maintained below More >

  • Open Access

    ARTICLE

    AI-Driven SDN and Blockchain-Based Routing Framework for Scalable and Trustworthy AIoT Networks

    Mekhled Alharbi1,*, Khalid Haseeb2, Mamoona Humayun3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.2, pp. 2601-2616, 2025, DOI:10.32604/cmes.2025.073039 - 26 November 2025

    Abstract Emerging technologies and the Internet of Things (IoT) are integrating for the growth and development of heterogeneous networks. These systems are providing real-time devices to end users to deliver dynamic services and improve human lives. Most existing approaches have been proposed to improve energy efficiency and ensure reliable routing; however, trustworthiness and network scalability remain significant research challenges. In this research work, we introduce an AI-enabled Software-Defined Network (SDN)- driven framework to provide secure communication, trusted behavior, and effective route maintenance. By considering multiple parameters in the forwarder selection process, the proposed framework enhances network More >

  • Open Access

    ARTICLE

    Real-Time and Energy-Aware UAV Routing: A Scalable DAR Approach for Future 6G Systems

    Khadija Slimani1,2,*, Samira Khoulji2, Hamed Taherdoost3,4, Mohamed Larbi Kerkeb5

    CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 4667-4686, 2025, DOI:10.32604/cmc.2025.070173 - 23 October 2025

    Abstract The integration of the dynamic adaptive routing (DAR) algorithm in unmanned aerial vehicle (UAV) networks offers a significant advancement in addressing the challenges posed by next-generation communication systems like 6G. DAR’s innovative framework incorporates real-time path adjustments, energy-aware routing, and predictive models, optimizing reliability, latency, and energy efficiency in UAV operations. This study demonstrated DAR’s superior performance in dynamic, large-scale environments, proving its adaptability and scalability for real-time applications. As 6G networks evolve, challenges such as bandwidth demands, global spectrum management, security vulnerabilities, and financial feasibility become prominent. DAR aligns with these demands by offering More >

  • Open Access

    ARTICLE

    A Genetic Algorithm-Based Double Auction Framework for Secure and Scalable Resource Allocation in Cloud-Integrated Intrusion Detection Systems

    Siraj Un Muneer1, Ihsan Ullah1, Zeshan Iqbal2,*, Rajermani Thinakaran3

    CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 4959-4975, 2025, DOI:10.32604/cmc.2025.068566 - 23 October 2025

    Abstract The complexity of cloud environments challenges secure resource management, especially for intrusion detection systems (IDS). Existing strategies struggle to balance efficiency, cost fairness, and threat resilience. This paper proposes an innovative approach to managing cloud resources through the integration of a genetic algorithm (GA) with a “double auction” method. This approach seeks to enhance security and efficiency by aligning buyers and sellers within an intelligent market framework. It guarantees equitable pricing while utilizing resources efficiently and optimizing advantages for all stakeholders. The GA functions as an intelligent search mechanism that identifies optimal combinations of bids More >

  • Open Access

    ARTICLE

    MBID: A Scalable Multi-Tier Blockchain Architecture with Physics-Informed Neural Networks for Intrusion Detection in Large-Scale IoT Networks

    Saeed Ullah1, Junsheng Wu1,*, Mian Muhammad Kamal2, Heba G. Mohamed3, Muhammad Sheraz4, Teong Chee Chuah4,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.2, pp. 2647-2681, 2025, DOI:10.32604/cmes.2025.068849 - 31 August 2025

    Abstract The Internet of Things (IoT) ecosystem faces growing security challenges because it is projected to have 76.88 billion devices by 2025 and $1.4 trillion market value by 2027, operating in distributed networks with resource limitations and diverse system architectures. The current conventional intrusion detection systems (IDS) face scalability problems and trust-related issues, but blockchain-based solutions face limitations because of their low transaction throughput (Bitcoin: 7 TPS (Transactions Per Second), Ethereum: 15–30 TPS) and high latency. The research introduces MBID (Multi-Tier Blockchain Intrusion Detection) as a groundbreaking Multi-Tier Blockchain Intrusion Detection System with AI-Enhanced Detection, which… More >

  • Open Access

    ARTICLE

    IECC-SAIN: Innovative ECC-Based Approach for Secure Authentication in IoT Networks

    Younes Lahraoui1, Jihane Jebrane2, Youssef Amal1, Saiida Lazaar1, Cheng-Chi Lee3,4,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.1, pp. 615-641, 2025, DOI:10.32604/cmes.2025.067778 - 31 July 2025

    Abstract Due to their resource constraints, Internet of Things (IoT) devices require authentication mechanisms that are both secure and efficient. Elliptic curve cryptography (ECC) meets these needs by providing strong security with shorter key lengths, which significantly reduces the computational overhead required for authentication algorithms. This paper introduces a novel ECC-based IoT authentication system utilizing our previously proposed efficient mapping and reverse mapping operations on elliptic curves over prime fields. By reducing reliance on costly point multiplication, the proposed algorithm significantly improves execution time, storage requirements, and communication cost across varying security levels. The proposed authentication… More >

  • Open Access

    ARTICLE

    Federated Learning and Blockchain Framework for Scalable and Secure IoT Access Control

    Ammar Odeh*, Anas Abu Taleb

    CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 447-461, 2025, DOI:10.32604/cmc.2025.065426 - 09 June 2025

    Abstract The increasing deployment of Internet of Things (IoT) devices has introduced significant security challenges, including identity spoofing, unauthorized access, and data integrity breaches. Traditional security mechanisms rely on centralized frameworks that suffer from single points of failure, scalability issues, and inefficiencies in real-time security enforcement. To address these limitations, this study proposes the Blockchain-Enhanced Trust and Access Control for IoT Security (BETAC-IoT) model, which integrates blockchain technology, smart contracts, federated learning, and Merkle tree-based integrity verification to enhance IoT security. The proposed model eliminates reliance on centralized authentication by employing decentralized identity management, ensuring tamper-proof… More >

  • Open Access

    ARTICLE

    Interpolation-Based Reversible Data Hiding in Encrypted Audio with Scalable Embedding Capacity

    Yuan-Yu Tsai1,*, Alfrindo Lin1, Wen-Ting Jao1, Yi-Hui Chen2,*

    CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 681-697, 2025, DOI:10.32604/cmc.2025.064370 - 09 June 2025

    Abstract With the rapid expansion of multimedia data, protecting digital information has become increasingly critical. Reversible data hiding offers an effective solution by allowing sensitive information to be embedded in multimedia files while enabling full recovery of the original data after extraction. Audio, as a vital medium in communication, entertainment, and information sharing, demands the same level of security as images. However, embedding data in encrypted audio poses unique challenges due to the trade-offs between security, data integrity, and embedding capacity. This paper presents a novel interpolation-based reversible data hiding algorithm for encrypted audio that achieves… More >

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