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  • Open Access

    ARTICLE

    MAIPFE: An Efficient Multimodal Approach Integrating Pre-Emptive Analysis, Personalized Feature Selection, and Explainable AI

    Moshe Dayan Sirapangi1, S. Gopikrishnan1,*

    CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2229-2251, 2024, DOI:10.32604/cmc.2024.047438

    Abstract Medical Internet of Things (IoT) devices are becoming more and more common in healthcare. This has created a huge need for advanced predictive health modeling strategies that can make good use of the growing amount of multimodal data to find potential health risks early and help individuals in a personalized way. Existing methods, while useful, have limitations in predictive accuracy, delay, personalization, and user interpretability, requiring a more comprehensive and efficient approach to harness modern medical IoT devices. MAIPFE is a multimodal approach integrating pre-emptive analysis, personalized feature selection, and explainable AI for real-time health… More >

  • Open Access

    ARTICLE

    Design Pattern and Challenges of Federated Learning with Applications in Industrial Control System

    Hina Batool1, Jiuyun Xu1,*, Ateeq Ur Rehman2, Habib Hamam3,4,5,6

    Journal on Artificial Intelligence, Vol.6, pp. 105-128, 2024, DOI:10.32604/jai.2024.049912

    Abstract Federated Learning (FL) appeared as an encouraging approach for handling decentralized data. Creating a FL system needs both machine learning (ML) knowledge and thinking about how to design system software. Researchers have focused a lot on the ML side of FL, but have not paid enough attention to designing the software architecture. So, in this survey, a set of design patterns is described to tackle the design issues. Design patterns are like reusable solutions for common problems that come up when designing software architecture. This paper focuses on (1) design patterns such as architectures, frameworks,… More >

  • Open Access

    REVIEW

    Recent Developments in Authentication Schemes Used in Machine-Type Communication Devices in Machine-to-Machine Communication: Issues and Challenges

    Shafi Ullah1, Sibghat Ullah Bazai1,*, Mohammad Imran2, Qazi Mudassar Ilyas3,*, Abid Mehmood4, Muhammad Asim Saleem5, Muhmmad Aasim Rafique3, Arsalan Haider6, Ilyas Khan7, Sajid Iqbal3, Yonis Gulzar4, Kauser Hameed3

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 93-115, 2024, DOI:10.32604/cmc.2024.048796

    Abstract Machine-to-machine (M2M) communication plays a fundamental role in autonomous IoT (Internet of Things)-based infrastructure, a vital part of the fourth industrial revolution. Machine-type communication devices (MTCDs) regularly share extensive data without human intervention while making all types of decisions. These decisions may involve controlling sensitive ventilation systems maintaining uniform temperature, live heartbeat monitoring, and several different alert systems. Many of these devices simultaneously share data to form an automated system. The data shared between machine-type communication devices (MTCDs) is prone to risk due to limited computational power, internal memory, and energy capacity. Therefore, securing the… More >

  • Open Access

    REVIEW

    Internet of Things Authentication Protocols: Comparative Study

    Souhayla Dargaoui1, Mourade Azrour1,*, Ahmad El Allaoui1, Azidine Guezzaz2, Abdulatif Alabdulatif3, Abdullah Alnajim4

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 65-91, 2024, DOI:10.32604/cmc.2024.047625

    Abstract Nowadays, devices are connected across all areas, from intelligent buildings and smart cities to Industry 4.0 and smart healthcare. With the exponential growth of Internet of Things usage in our world, IoT security is still the biggest challenge for its deployment. The main goal of IoT security is to ensure the accessibility of services provided by an IoT environment, protect privacy, and confidentiality, and guarantee the safety of IoT users, infrastructures, data, and devices. Authentication, as the first line of defense against security threats, becomes the priority of everyone. It can either grant or deny… More >

  • Open Access

    ARTICLE

    An Ingenious IoT Based Crop Prediction System Using ML and EL

    Shabana Ramzan1, Yazeed Yasin Ghadi2, Hanan Aljuaid3, Aqsa Mahmood1,*, Basharat Ali4

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 183-199, 2024, DOI:10.32604/cmc.2024.047603

    Abstract Traditional farming procedures are time-consuming and expensive as based on manual labor. Farmers have no proper knowledge to select which crop is suitable to grow according to the environmental factors and soil characteristics. This is the main reason for the low yield of crops and the economic crisis in the agricultural sector of the different countries. The use of modern technologies such as the Internet of Things (IoT), machine learning, and ensemble learning can facilitate farmers to observe different factors such as soil electrical conductivity (EC), and environmental factors like temperature to improve crop yield.… More >

  • Open Access

    ARTICLE

    ResNeSt-biGRU: An Intrusion Detection Model Based on Internet of Things

    Yan Xiang1,2, Daofeng Li1,2,*, Xinyi Meng1,2, Chengfeng Dong1,2, Guanglin Qin1,2

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1005-1023, 2024, DOI:10.32604/cmc.2024.047143

    Abstract The rapid expansion of Internet of Things (IoT) devices across various sectors is driven by steadily increasing demands for interconnected and smart technologies. Nevertheless, the surge in the number of IoT device has caught the attention of cyber hackers, as it provides them with expanded avenues to access valuable data. This has resulted in a myriad of security challenges, including information leakage, malware propagation, and financial loss, among others. Consequently, developing an intrusion detection system to identify both active and potential intrusion traffic in IoT networks is of paramount importance. In this paper, we propose… More >

  • Open Access

    ARTICLE

    The Influence of Internet Use on Women’s Depression and Its Countermeasures—Empirical Analysis Based on Data from CFPS

    Dengke Xu1, Linlin Shen1, Fangzhong Xu2,*

    International Journal of Mental Health Promotion, Vol.26, No.3, pp. 229-238, 2024, DOI:10.32604/ijmhp.2024.046023

    Abstract Based on China Family Panel Studies (CFPS) 2018 data, the multiple linear regression model is used to analyze the effects of Internet use on women’s depression, and to test the robustness of the regression results. At the same time, the effects of Internet use on mental health of women with different residence, age, marital status and physical health status are analyzed. Then, we can obtain that Internet use has a significant promoting effect on women’s mental health, while the degree of Internet use has a significant inhibitory effect on women’s mental health. In addition, the… More >

  • Open Access

    ARTICLE

    A Hybrid and Lightweight Device-to-Server Authentication Technique for the Internet of Things

    Shaha Al-Otaibi1, Rahim Khan2,*, Hashim Ali2, Aftab Ahmed Khan2, Amir Saeed3, Jehad Ali4,*

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3805-3823, 2024, DOI:10.32604/cmc.2024.049017

    Abstract The Internet of Things (IoT) is a smart networking infrastructure of physical devices, i.e., things, that are embedded with sensors, actuators, software, and other technologies, to connect and share data with the respective server module. Although IoTs are cornerstones in different application domains, the device’s authenticity, i.e., of server(s) and ordinary devices, is the most crucial issue and must be resolved on a priority basis. Therefore, various field-proven methodologies were presented to streamline the verification process of the communicating devices; however, location-aware authentication has not been reported as per our knowledge, which is a crucial… More >

  • Open Access

    ARTICLE

    A Security Trade-Off Scheme of Anomaly Detection System in IoT to Defend against Data-Tampering Attacks

    Bing Liu1, Zhe Zhang1, Shengrong Hu2, Song Sun3,*, Dapeng Liu4, Zhenyu Qiu5

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 4049-4069, 2024, DOI:10.32604/cmc.2024.048099

    Abstract Internet of Things (IoT) is vulnerable to data-tampering (DT) attacks. Due to resource limitations, many anomaly detection systems (ADSs) for IoT have high false positive rates when detecting DT attacks. This leads to the misreporting of normal data, which will impact the normal operation of IoT. To mitigate the impact caused by the high false positive rate of ADS, this paper proposes an ADS management scheme for clustered IoT. First, we model the data transmission and anomaly detection in clustered IoT. Then, the operation strategy of the clustered IoT is formulated as the running probabilities… More >

  • Open Access

    ARTICLE

    RL and AHP-Based Multi-Timescale Multi-Clock Source Time Synchronization for Distribution Power Internet of Things

    Jiangang Lu, Ruifeng Zhao*, Zhiwen Yu, Yue Dai, Kaiwen Zeng

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 4453-4469, 2024, DOI:10.32604/cmc.2024.048020

    Abstract Time synchronization (TS) is crucial for ensuring the secure and reliable functioning of the distribution power Internet of Things (IoT). Multi-clock source time synchronization (MTS) has significant advantages of high reliability and accuracy but still faces challenges such as optimization of the multi-clock source selection and the clock source weight calculation at different timescales, and the coupling of synchronization latency jitter and pulse phase difference. In this paper, the multi-timescale MTS model is conducted, and the reinforcement learning (RL) and analytic hierarchy process (AHP)-based multi-timescale MTS algorithm is designed to improve the weighted summation of More >

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