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Blocking without Breaking: Identification and Mitigation of Non-Essential IoT Traffic

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abstract

Despite the prevalence of Internet of Things (IoT) devices, there is little information about the purpose and risks of the Internet traffic these devices generate, and consumers have limited options for controlling those risks. A key open question is whether one can mitigate these risks by automatically blocking some of the Internet connections from IoT devices, without rendering the devices inoperable. In this paper, we address this question by developing a rigorous methodology that relies on automated IoT-device experimentation to reveal which network connections (and the information they expose) are essential, and which are not. We further develop strategies to automatically classify network traffic destinations as either required (i.e., their traffic is essential for devices to work properly) or not, hence allowing firewall rules to block traffic sent to non-required destinations without breaking the functionality of the device. We find that indeed 16 among the 31 devices we tested have at least one blockable non-required destination, with the maximum number of blockable destinations for a device being 11. We further analyze the destination of network traffic and find that all third parties observed in our experiments are blockable, while first and support parties are neither uniformly required or non-required. Finally, we demonstrate the limitations of existing blocklists on IoT traffic, propose a set of guidelines for automatically limiting non-essential IoT traffic, and we develop a prototype system that implements these guidelines.

fields

cs.CR 1

years

2025 1

verdicts

CONDITIONAL 1

representative citing papers

Intelligent Detection of Non-Essential IoT Traffic on the Home Gateway

cs.CR · 2025-04-22 · conditional · novelty 6.0

ML-IoTrim uses random forests and neural networks on per-destination traffic statistics to distinguish essential from non-essential IoT destinations, achieving near-perfect accuracy on seen devices but not on unseen device types.

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  • Intelligent Detection of Non-Essential IoT Traffic on the Home Gateway cs.CR · 2025-04-22 · conditional · none · ref 16 · internal anchor

    ML-IoTrim uses random forests and neural networks on per-destination traffic statistics to distinguish essential from non-essential IoT destinations, achieving near-perfect accuracy on seen devices but not on unseen device types.