View article

As more and more devices are connected to the Internet-of-Things, often made by non-specialist companies or short-lived startups, the likelihood that these devices will be hacked and used for nefarious activity online increases. We seek to support non-expert users in managing the network behaviour of their IoT devices, and assisting them in handling the cases where those devices are hacked. To do so, we wish to enable anomaly detection at the network level, determining when a device starts behaving unusually. This requires capturing data about how devices behave in a diverse range of real deployments, not just lab environments.

To that end, we present IoTCrowdsourcery, a toolset for capturing traffic data from real-world IoT deployments. Participants collect packet traces from their IoT devices through our software, and provide them via a crowdsourcing infrastructure. The key challenges to overcome are to …