Automatic Malware Detection on an Alexa-Pi IoT Device

This work explores some of the security concerns pertaining to running software similar to Amazon Alexa home assistant on IoT-like platforms. We implement a behavioral-based malware detector and compare the effectiveness of different system attributes that are used in detecting malware, i.e., system calls, network traffic, and the integration of system call and network traffic features. Given the small number of malware samples for IoT devices, we create a parameterizable malware sample that mimics Alexa behavior to varying degrees, while exfiltrating data from the device to a remote host. The performance of our anomaly detector is evaluated based on how well it determines the presence of our parameterized malware on an Alexa-enabled IoT device.