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How do we do malware analysis for Non-Windows based datasets? In the Internet of Things, a good percentage of devices are neither windows based, nor Linux nor Mac nor Android. They are sensor and actuators perhaps in RIOT and other Operating systems meant for non x86/x64 platforms.

How to analyze this malware and are there datasets open for IoT Malware?

Does the CPU architecture of the resident device influence the malware analysis in the test environment? more so the embedded such ARM architectures

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Generally, for malware analysis, there are 2 different approaches. Security Developers try to hunt malware according to their static and dynamic features. As I know all of the IoT malware analysis techniques are using static features and they are based on the OPCODEs generated by the malware.

The other approach is based on dynamic features of the malwares. Dynamic features are the behavioral characteristics of the softwares when they are running. For example api calls or permission requests of the software. Generally to investigate the dynamic features you may need to run the malware in a secure environment like sandbox. However; as i know there is no the dynamic feature based approach for IoT ecosystem.

Lastly, yes, there is only one IoT malware dataset based on ARM architecture.

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    So, what is the other approach?
    – schroeder
    Commented Jan 21, 2021 at 13:02
  • The other approach is based on dynamic features of the malwares. Dynamic features are the behavioral characteristics of the softwares when they are running. For example api calls or permission requests of the software. Generally to investigate the dynamic features you may need to run the malware in a secure environment like sandbox. However; as i know there is no the dynamic feature based approach for IoT ecosystem. Commented Jan 22, 2021 at 14:41
  • can you edit the post to include these details?
    – schroeder
    Commented Jan 22, 2021 at 15:55

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