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  • Open Access

    ARTICLE

    SNN-IoMT: A Novel AI-Driven Model for Intrusion Detection in Internet of Medical Things

    Mourad Benmalek1,*,#,*, Abdessamed Seddiki2,#, Kamel-Dine Haouam1

    CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.1, pp. 1157-1184, 2025, DOI:10.32604/cmes.2025.062841 - 11 April 2025

    Abstract The Internet of Medical Things (IoMT) connects healthcare devices and sensors to the Internet, driving transformative advancements in healthcare delivery. However, expanding IoMT infrastructures face growing security threats, necessitating robust Intrusion Detection Systems (IDS). Maintaining the confidentiality of patient data is critical in AI-driven healthcare systems, especially when securing interconnected medical devices. This paper introduces SNN-IoMT (Stacked Neural Network Ensemble for IoMT Security), an AI-driven IDS framework designed to secure dynamic IoMT environments. Leveraging a stacked deep learning architecture combining Multi-Layer Perceptron (MLP), Convolutional Neural Networks (CNN), and Long Short-Term Memory (LSTM), the model optimizes data management More >

  • Open Access

    ARTICLE

    LSBSP: A Lightweight Sharding Method of Blockchain Based on State Pruning for Efficient Data Sharing in IoMT

    Guoqiong Liao1,3, Yinxiang Lei1,2,*, Yufang Xie1, Neal N. Xiong4

    CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 3309-3335, 2025, DOI:10.32604/cmc.2024.060077 - 17 February 2025

    Abstract As the Internet of Medical Things (IoMT) continues to expand, smart health-monitoring devices generate vast amounts of valuable data while simultaneously raising critical security and privacy challenges. Blockchain technology presents a promising avenue to address these concerns due to its inherent decentralization and security features. However, scalability remains a persistent hurdle, particularly for IoMT applications that involve large-scale networks and resource-constrained devices. This paper introduces a novel lightweight sharding method tailored to the unique demands of IoMT data sharing. Our approach enhances state bootstrapping efficiency and reduces operational overhead by utilizing a dual-chain structure comprising… 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

    Transforming Healthcare: AI-NLP Fusion Framework for Precision Decision-Making and Personalized Care Optimization in the Era of IoMT

    Soha Rawas1, Cerine Tafran1, Duaa AlSaeed2, Nadia Al-Ghreimil2,*

    CMC-Computers, Materials & Continua, Vol.81, No.3, pp. 4575-4601, 2024, DOI:10.32604/cmc.2024.055307 - 19 December 2024

    Abstract In the rapidly evolving landscape of healthcare, the integration of Artificial Intelligence (AI) and Natural Language Processing (NLP) holds immense promise for revolutionizing data analytics and decision-making processes. Current techniques for personalized medicine, disease diagnosis, treatment recommendations, and resource optimization in the Internet of Medical Things (IoMT) vary widely, including methods such as rule-based systems, machine learning algorithms, and data-driven approaches. However, many of these techniques face limitations in accuracy, scalability, and adaptability to complex clinical scenarios. This study investigates the synergistic potential of AI-driven optimization techniques and NLP applications in the context of the… More >

  • Open Access

    ARTICLE

    Augmenting Internet of Medical Things Security: Deep Ensemble Integration and Methodological Fusion

    Hamad Naeem1, Amjad Alsirhani2,*, Faeiz M. Alserhani3, Farhan Ullah4, Ondrej Krejcar1

    CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.3, pp. 2185-2223, 2024, DOI:10.32604/cmes.2024.056308 - 31 October 2024

    Abstract When it comes to smart healthcare business systems, network-based intrusion detection systems are crucial for protecting the system and its networks from malicious network assaults. To protect IoMT devices and networks in healthcare and medical settings, our proposed model serves as a powerful tool for monitoring IoMT networks. This study presents a robust methodology for intrusion detection in Internet of Medical Things (IoMT) environments, integrating data augmentation, feature selection, and ensemble learning to effectively handle IoMT data complexity. Following rigorous preprocessing, including feature extraction, correlation removal, and Recursive Feature Elimination (RFE), selected features are standardized… More >

  • Open Access

    REVIEW

    IoMT-Based Healthcare Systems: A Review

    Tahir Abbas1,*, Ali Haider Khan2, Khadija Kanwal3, Ali Daud4,*, Muhammad Irfan5, Amal Bukhari6, Riad Alharbey6

    Computer Systems Science and Engineering, Vol.48, No.4, pp. 871-895, 2024, DOI:10.32604/csse.2024.049026 - 17 July 2024

    Abstract The integration of the Internet of Medical Things (IoMT) and the Internet of Things (IoT), which has revolutionized patient care through features like remote critical care and real-time therapy, is examined in this study in response to the changing healthcare landscape. Even with these improvements, security threats are associated with the increased connectivity of medical equipment, which calls for a thorough assessment. With a primary focus on addressing security and performance enhancement challenges, the research classifies current IoT communication devices, examines their applications in IoMT, and investigates important aspects of IoMT devices in healthcare. The More >

  • Open Access

    ARTICLE

    Vector Dominance with Threshold Searchable Encryption (VDTSE) for the Internet of Things

    Jingjing Nie1,*, Zhenhua Chen2

    CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 4763-4779, 2024, DOI:10.32604/cmc.2024.051181 - 20 June 2024

    Abstract The Internet of Medical Things (IoMT) is an application of the Internet of Things (IoT) in the medical field. It is a cutting-edge technique that connects medical sensors and their applications to healthcare systems, which is essential in smart healthcare. However, Personal Health Records (PHRs) are normally kept in public cloud servers controlled by IoMT service providers, so privacy and security incidents may be frequent. Fortunately, Searchable Encryption (SE), which can be used to execute queries on encrypted data, can address the issue above. Nevertheless, most existing SE schemes cannot solve the vector dominance threshold… More >

  • Open Access

    ARTICLE

    DNBP-CCA: A Novel Approach to Enhancing Heterogeneous Data Traffic and Reliable Data Transmission for Body Area Network

    Abdulwadood Alawadhi1,*, Mohd. Hasbullah Omar1, Abdullah Almogahed2, Noradila Nordin3, Salman A. Alqahtani4, Atif M. Alamri5

    CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2851-2878, 2024, DOI:10.32604/cmc.2024.050154 - 15 May 2024

    Abstract The increased adoption of Internet of Medical Things (IoMT) technologies has resulted in the widespread use of Body Area Networks (BANs) in medical and non-medical domains. However, the performance of IEEE 802.15.4-based BANs is impacted by challenges related to heterogeneous data traffic requirements among nodes, including contention during finite backoff periods, association delays, and traffic channel access through clear channel assessment (CCA) algorithms. These challenges lead to increased packet collisions, queuing delays, retransmissions, and the neglect of critical traffic, thereby hindering performance indicators such as throughput, packet delivery ratio, packet drop rate, and packet delay.… More >

  • Open Access

    ARTICLE

    Machine Learning-Enabled Communication Approach for the Internet of Medical Things

    Rahim Khan1,3, Abdullah Ghani1, Samia Allaoua Chelloug2,*, Mohammed Amin4, Aamir Saeed5, Jason Teo1

    CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 1569-1584, 2023, DOI:10.32604/cmc.2023.039859 - 30 August 2023

    Abstract The Internet of Medical Things (IoMT) is mainly concerned with the efficient utilisation of wearable devices in the healthcare domain to manage various processes automatically, whereas machine learning approaches enable these smart systems to make informed decisions. Generally, broadcasting is used for the transmission of frames, whereas congestion, energy efficiency, and excessive load are among the common issues associated with existing approaches. In this paper, a machine learning-enabled shortest path identification scheme is presented to ensure reliable transmission of frames, especially with the minimum possible communication overheads in the IoMT network. For this purpose, the… More >

  • Open Access

    ARTICLE

    Priority Detector and Classifier Techniques Based on ML for the IoMT

    Rayan A. Alsemmeari1,*, Mohamed Yehia Dahab2, Badraddin Alturki1, Abdulaziz A. Alsulami3

    CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 1853-1870, 2023, DOI:10.32604/cmc.2023.038589 - 30 August 2023

    Abstract Emerging telemedicine trends, such as the Internet of Medical Things (IoMT), facilitate regular and efficient interactions between medical devices and computing devices. The importance of IoMT comes from the need to continuously monitor patients’ health conditions in real-time during normal daily activities, which is realized with the help of various wearable devices and sensors. One major health problem is workplace stress, which can lead to cardiovascular disease or psychiatric disorders. Therefore, real-time monitoring of employees’ stress in the workplace is essential. Stress levels and the source of stress could be detected early in the fog… More >

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