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Traditional techniques to detect malware infections were not meant to be usedby the end-user and current malware removal tools and security software cannothandle the heterogeneity of IoT devices. In this paper, we design, develop andevaluate a tool, called NURSE, to fill this information gap, i.e., enablingend-users to detect IoT-malware infections in their home networks. NURSEfollows a modular approach to analyze IoT traffic as captured by means of anARP spoofing technique which does not require any network modification orspecific hardware. Thus, NURSE provides zero-configuration IoT traffic analysiswithin everybody's reach. After testing NURSE in 83 different IoT networkscenarios with a wide variety of IoT device types, results show that NURSEidentifies malware-infected IoT devices with high accuracy (86.7%) using devicenetwork behavior and contacted destinations.

NURSE: eNd-UseR IoT malware detection tool for Smart homEs