基于可执行文件字节序列的物联网恶意软件检测

Tzu-Ling Wan, Tao Ban, Yen-Ting Lee, Shin-Ming Cheng, Ryoichi Isawa, Takeshi Takahashi, D. Inoue
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引用次数: 12

摘要

针对物联网(IoT)设备的攻击正在上升。为了预防和对抗物联网恶意软件,我们提出了一种基于直接从ELF二进制文件中提取的静态判别信息的物联网恶意软件程序跨平台分析。通过对由7种不同CPU架构的超过222K个样本组成的数据集进行实验,我们证明了有效的恶意软件检测可以以接近最佳的精度实现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
IoT-Malware Detection Based on Byte Sequences of Executable Files
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.
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