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    ARTICLE

    Massive IoT Malware Classification Method Using Binary Lifting

    Hae-Seon Jeong1, Jin Kwak2,*

    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 467-481, 2022, DOI:10.32604/iasc.2022.021038 - 26 October 2021

    Abstract Owing to the development of next-generation network and data processing technologies, massive Internet of Things (IoT) devices are becoming hyperconnected. As a result, Linux malware is being created to attack such hyperconnected networks by exploiting security threats in IoT devices. To determine the potential threats of such Linux malware and respond effectively, malware classification through an analysis of the executed code is required; however, a limitation exists in that each heterogeneous architecture must be analyzed separately. However, the binary codes of a heterogeneous architecture can be translated to a high-level intermediate representation (IR) of the More >

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