Preliminary Results on Exploring Data Exhaust of Consumer Internet of Things Devices

In this paper, we apply a machine learning classifier to the publicly available consumer Internet of Things (IoT) traffic traces to explore the nature and extent of any potential data exhaust. To this end, we propose two feature sets and compare them against the baseline flow feature set and the results from the previous works. Evaluations show the improvement in performance obtained using the proposed feature sets and the variety of information that can be extracted from the captured IoT traffic regardless of encryption.