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  • Open Access

    ARTICLE

    An Efficient Scheme for Interference Mitigation in 6G-IoT Wireless Networks

    Fahd N. Al-Wesabi1,*, Imran Khan2, Nadhem Nemri3, Mohammed A. Al-Hagery4, Huda G. Iskander5, Quang Ngoc Nguyen6, Babar Shah7, Ki-Il Kim8

    CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3889-3902, 2021, DOI:10.32604/cmc.2021.016218

    Abstract The Internet of Things (IoT) is the fourth technological revolution in the global information industry after computers, the Internet, and mobile communication networks. It combines radio-frequency identification devices, infrared sensors, global positioning systems, and various other technologies. Information sensing equipment is connected via the Internet, thus forming a vast network. When these physical devices are connected to the Internet, the user terminal can be extended and expanded to exchange information, communicate with anything, and carry out identification, positioning, tracking, monitoring, and triggering of corresponding events on each device in the network. In real life, the IoT has a wide range… More >

  • Open Access

    ARTICLE

    DeepIoT.IDS: Hybrid Deep Learning for Enhancing IoT Network Intrusion Detection

    Ziadoon K. Maseer1, Robiah Yusof1, Salama A. Mostafa2,*, Nazrulazhar Bahaman1, Omar Musa3, Bander Ali Saleh Al-rimy4

    CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3945-3966, 2021, DOI:10.32604/cmc.2021.016074

    Abstract With an increasing number of services connected to the internet, including cloud computing and Internet of Things (IoT) systems, the prevention of cyberattacks has become more challenging due to the high dimensionality of the network traffic data and access points. Recently, researchers have suggested deep learning (DL) algorithms to define intrusion features through training empirical data and learning anomaly patterns of attacks. However, due to the high dynamics and imbalanced nature of the data, the existing DL classifiers are not completely effective at distinguishing between abnormal and normal behavior line connections for modern networks. Therefore, it is important to design… More >

  • Open Access

    ARTICLE

    The Data Acquisition and Control System Based on IoT-CAN Bus

    He Gong1,2,3,4, Ji Li1, RuiWen Ni1, Pei Xiao1, Hang Ouyang1, Ye Mu1,*, Thobela Louis Tyasi5

    Intelligent Automation & Soft Computing, Vol.30, No.3, pp. 1049-1062, 2021, DOI:10.32604/iasc.2021.019730

    Abstract Presently, the adoption of Internet of things(IOT)-related technologies in the Smart Farming domain is rapidly emerging. The increasing number of sensors used in diverse applications has provided a massive number of continuous, unbounded, rapid data and requires the management of distinct protocols, interfaces and intermittent connections. A low-cost, low-power, and low data-rate solution is proposed to fulfill the requirements of information monitoring for actual large-scale agricultural farms, which we will need pressingly in the future. This paper designs a heterogeneous data acquisition and control system for differentiated agricultural information monitoring terminal. Based on the IoT-CAN bus architecture, the system can… More >

  • Open Access

    ARTICLE

    Performance Comparison of PoseNet Models on an AIoT Edge Device

    Min-Jun Kim1, Seng-Phil Hong2, Mingoo Kang1, Jeongwook Seo1,*

    Intelligent Automation & Soft Computing, Vol.30, No.3, pp. 743-753, 2021, DOI:10.32604/iasc.2021.019329

    Abstract In this paper, we present an oneM2M-compliant system including an artificial intelligence of things (AIoT) edge device whose principal function is to estimate human poses by using two PoseNet models built on MobileNet v1 and ResNet-50 backbone architectures. Although MobileNet v1 is generally known to be much faster but less accurate than ResNet50, it is necessary to analyze the performances of whole PoseNet models carefully and select one of them suitable for the AIoT edge device. For this reason, we first investigate the computational complexity of the models about their neural network layers and parameters and then compare their performances… More >

  • Open Access

    ARTICLE

    A Resource-constrained Edge IoT Device Data-deduplication Method with Dynamic Asymmetric Maximum

    Ye Yang1, Xiaofang Li2, Dongjie Zhu3,*, Hao Hu3, Haiwen Du4, Yundong Sun4, Weiguo Tian3, Yansong Wang3, Ning Cao1, Gregory M.P. O’Hare5

    Intelligent Automation & Soft Computing, Vol.30, No.2, pp. 481-494, 2021, DOI:10.32604/iasc.2021.019201

    Abstract Smart vehicles use sophisticated sensors to capture real-time data. Due to the weak communication capabilities of wireless sensors, these data need to upload to the cloud for processing. Sensor clouds can resolve these drawbacks. However, there is a large amount of redundant data in the sensor cloud, occupying a large amount of storage space and network bandwidth. Deduplication can yield cost savings by storing one data copy. Chunking is essential because it can determine the performance of deduplication. Content-Defined Chunking (CDC) can effectively solve the problem of chunk boundaries shifted, but it occupies a lot of computing resources and has… More >

  • Open Access

    ARTICLE

    Security Empowered System-on-Chip Selection for Internet of Things

    Ramesh Krishnamoorthy*, Kalimuthu Krishnan

    Intelligent Automation & Soft Computing, Vol.30, No.2, pp. 403-418, 2021, DOI:10.32604/iasc.2021.018560

    Abstract Due to the rapid growth of embedded devices, the selection of System-on-Chip (SoC) has a stronger influence to enable hardware security in embedded system design. System-on-chip (SoC) devices consist of one or more CPUs through wide-ranging inbuilt peripherals for designing a system with less cost. The selection of SoC is more significant to determine the suitability for secured application development. The design space analysis of symmetric key approaches including rivest cipher (RC5), advanced encryption standard (AES), data encryption standard (DES), international data encryption algorithm (IDEA), elliptic curve cryptography (ECC), MX algorithm, and the secure hash algorithm (SHA-256) are compared to… More >

  • Open Access

    REVIEW

    Multi-Disease Prediction Based on Deep Learning: A Survey

    Shuxuan Xie, Zengchen Yu, Zhihan Lv*

    CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.2, pp. 489-522, 2021, DOI:10.32604/cmes.2021.016728

    Abstract In recent years, the development of artificial intelligence (AI) and the gradual beginning of AI’s research in the medical field have allowed people to see the excellent prospects of the integration of AI and healthcare. Among them, the hot deep learning field has shown greater potential in applications such as disease prediction and drug response prediction. From the initial logistic regression model to the machine learning model, and then to the deep learning model today, the accuracy of medical disease prediction has been continuously improved, and the performance in all aspects has also been significantly improved. This article introduces some… More >

  • Open Access

    ARTICLE

    A Lightweight Blockchain for IoT in Smart City (IoT-SmartChain)

    Zakariae Dlimi*, Abdellah Ezzati, Saïd Ben Alla

    CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2687-2703, 2021, DOI:10.32604/cmc.2021.018942

    Abstract The smart city is a technological framework that connects the city’s different components to create new opportunities. This connection is possible with the help of the Internet of Things (IoT), which provides a digital personality to physical objects. Some studies have proposed integrating Blockchain technology with IoT in different use cases as access, orchestration, or replicated storage layer. The majority of connected objects’ capacity limitation makes the use of Blockchain inadequate due to its redundancy and its conventional processing-intensive consensus like PoW. This paper addresses these challenges by proposing a NOVEL model of a lightweight Blockchain framework (IoT-SmartChain), with a… More >

  • Open Access

    ARTICLE

    Intelligent Microservice Based on Blockchain for Healthcare Applications

    Faisal Jamil1, Faiza Qayyum1, Soha Alhelaly2, Farjeel Javed3, Ammar Muthanna4,5,*

    CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2513-2530, 2021, DOI:10.32604/cmc.2021.018809

    Abstract Nowadays, the blockchain, Internet of Things, and artificial intelligence technology revolutionize the traditional way of data mining with the enhanced data preprocessing, and analytics approaches, including improved service platforms. Nevertheless, one of the main challenges is designing a combined approach that provides the analytics functionality for diverse data and sustains IoT applications with robust and modular blockchain-enabled services in a diverse environment. Improved data analytics model not only provides support insights in IoT data but also fosters process productivity. Designing a robust IoT-based secure analytic model is challenging for several purposes, such as data from diverse sources, increasing data size,… More >

  • Open Access

    ARTICLE

    A Lightweight Certificate-Based Aggregate Signature Scheme Providing Key Insulation

    Yong-Woon Hwang, Im-Yeong Lee*

    CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1747-1764, 2021, DOI:10.32604/cmc.2021.018549

    Abstract Recently, with the advancement of Information and Communications Technology (ICT), Internet of Things (IoT) has been connected to the cloud and used in industrial sectors, medical environments, and smart grids. However, if data is transmitted in plain text when collecting data in an IoT-cloud environment, it can be exposed to various security threats such as replay attacks and data forgery. Thus, digital signatures are required. Data integrity is ensured when a user (or a device) transmits data using a signature. In addition, the concept of data aggregation is important to efficiently collect data transmitted from multiple users (or a devices)… More >

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