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  • Open Access

    ARTICLE

    Intrusion Detection Method of Internet of Things Based on Multi GBDT Feature Dimensionality Reduction and Hierarchical Traffic Detection

    Taifeng Pan*

    Journal of Quantum Computing, Vol.3, No.4, pp. 161-171, 2021, DOI:10.32604/jqc.2021.025373 - 10 January 2022

    Abstract The rapid development of Internet of Things (IoT) technology has brought great convenience to people’s life. However, the security protection capability of IoT is weak and vulnerable. Therefore, more protection needs to be done for the security of IoT. The paper proposes an intrusion detection method for IoT based on multi GBDT feature reduction and hierarchical traffic detection model. Firstly, GBDT is used to filter the features of IoT traffic data sets BoT-IoT and UNSW-NB15 to reduce the traffic feature dimension. At the same time, in order to improve the reliability of feature filtering, this… More >

  • Open Access

    ARTICLE

    Security Analysis of Smart Speaker: Security Attacks and Mitigation

    Youngseok Park1, Hyunsang Choi1, Sanghyun Cho1, Young-Gab Kim2,*

    CMC-Computers, Materials & Continua, Vol.61, No.3, pp. 1075-1090, 2019, DOI:10.32604/cmc.2019.08520

    Abstract The speech recognition technology has been increasingly common in our lives. Recently, a number of commercial smart speakers containing the personal assistant system using speech recognition came out. While the smart speaker vendors have been concerned about the intelligence and the convenience of their assistants, but there have been little mentions of the smart speakers in security aspects. As the smart speakers are becoming the hub for home automation, its security vulnerabilities can cause critical problems. In this paper, we categorize attack vectors and classify them into hardware-based, network-based, and software-based. With the attack vectors, More >

  • Open Access

    ARTICLE

    A Novel Ensemble Learning Algorithm Based on D-S Evidence Theory for IoT Security

    Changting Shi1, *

    CMC-Computers, Materials & Continua, Vol.57, No.3, pp. 635-652, 2018, DOI:10.32604/cmc.2018.03754

    Abstract In the last decade, IoT has been widely used in smart cities, autonomous driving and Industry 4.0, which lead to improve efficiency, reliability, security and economic benefits. However, with the rapid development of new technologies, such as cognitive communication, cloud computing, quantum computing and big data, the IoT security is being confronted with a series of new threats and challenges. IoT device identification via Radio Frequency Fingerprinting (RFF) extracting from radio signals is a physical-layer method for IoT security. In physical-layer, RFF is a unique characteristic of IoT device themselves, which can difficultly be tampered. More >

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