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IoT-Malware Detection Based on Byte Sequences of Executable Files

机译:基于可执行文件字节序列的物联网恶意软件检测

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Attacks towards the Internet of Things (IoT) devices are on the rise. To enable precaution and countermeasure against IoT malware, we present a cross-platform analysis of IoT malware programs based on static discriminating information extracted directly from ELF binaries. With experiments on a dataset composed of more than 222K samples cross 7 different CPU architectures, we demonstrate that efficient malware detection can be realized with near optimal accuracy.
机译:对物联网(IoT)设备的攻击正在增加。为了针对物联网恶意软件采取预防措施,我们基于直接从ELF二进制文件中提取的静态区分信息,对物联网恶意软件程序进行了跨平台分析。通过在7个不同CPU架构上由超过222K样本组成的数据集上进行的实验,我们证明了可以以接近最佳的精度实现有效的恶意软件检测。

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