The weakness of the security measures implemented on IoT devices, added to the sensitivity of the data that they handle, has created an attractive environment for cybercriminals to carry out attacks. To do so, they develop malware to compromise devices and control them. The study of malware samples is a crucial task in order to gain information on how to protect these devices, but it is impossible to manually do this due to the immense number of existing samples. Moreover, in the IoT, coexist multiple hardware architectures, such as ARM, PowerPC, MIPS, Intel 8086, or x64-86, which enlarges even more the quantity of malicious software. In this article, a modular solution to automatically analyze IoT malware samples from these architectures is proposed. In addition, the proposal is subjected to evaluation, analyzing a testbed of 1500 malware samples, proving that it is an effective approach to rapidly examining malicious software compiled for any architecture.

中文翻译：

---

物联网恶意软件样本的安全和通信网络自动分析架构

在物联网设备上实施的安全措施的弱点，再加上它们处理的数据的敏感性，为网络罪犯创造了诱人的环境以进行攻击。为此，他们开发了恶意软件来破坏设备并对其进行控制。为了获得有关如何保护这些设备的信息，对恶意软件样本的研究是一项至关重要的任务，但是由于存在大量现有样本，因此无法手动执行此操作。此外，在物联网中，多种硬件架构共存，例如ARM，PowerPC，MIPS，Intel 8086或x64-86，这会进一步增加恶意软件的数量。在本文中，提出了一种模块化解决方案，用于自动分析来自这些架构的IoT恶意软件样本。此外，该提案还需要进行评估，分析1500个恶意软件样本的测试平台，