The Forest Behind the Tree: Revealing Hidden Smart Home Communication Patterns
François De Keersmaeker , Rémi Van Boxem , Cristel Pelsser and Ramin Sadre
Abstract
The widespread use of Smart Home devices has attracted significant research interest in understanding their behavior within home networks. Unlike general-purpose computers, these devices exhibit relatively simple and predictable network activity patterns. However, previous studies have primarily focused on normal network conditions, overlooking potential hidden patterns that emerge under challenging conditions. Discovering the latter is crucial for assessing device robustness. This paper addresses this gap by presenting a framework that systematically and automatically reveals these hidden communication patterns. By actively disturbing communication and blocking observed traffic, the framework generates comprehensive profiles structured as behavior trees, uncovering traffic flows that are missed by more shallow methods. This approach was applied to ten real-world devices, identifying 254 unique flows, with over 27% only discovered through this new method. These insights enhance our understanding of device robustness, and the thus obtained profiles provide a more complete description of the network behavior of devices, as needed, for example, for the configuration of security solutions.
Publication Details
- Publication Type
- Conference Paper
- Publication Date
- September 2025
- Published In
- Proceedings of the 33rd IEEE International Conference on Network Protocols (ICNP '25)
- Location
- Seoul, South Korea
- External Link
- http://hdl.handle.net/2078.1/304200
BibTeX Citation
@inproceedings{Keersmaeker2025,
title = {The Forest Behind the Tree: Revealing Hidden Smart Home Communication Patterns},
author = {François De Keersmaeker and Rémi Van Boxem and Cristel Pelsser and Ramin Sadre},
year = 2025,
month = sep,
booktitle = {Proceedings of the 33rd IEEE International Conference on Network Protocols ({ICNP} '25)},
address = {Seoul, South Korea},
url = {http://hdl.handle.net/2078.1/304200},
organization = {IEEE},
abstract = {The widespread use of Smart Home devices has attracted significant research interest in understanding their behavior within home networks. Unlike general-purpose computers, these devices exhibit relatively simple and predictable network activity patterns. However, previous studies have primarily focused on normal network conditions, overlooking potential hidden patterns that emerge under challenging conditions. Discovering the latter is crucial for assessing device robustness. This paper addresses this gap by presenting a framework that systematically and automatically reveals these hidden communication patterns. By actively disturbing communication and blocking observed traffic, the framework generates comprehensive profiles structured as behavior trees, uncovering traffic flows that are missed by more shallow methods. This approach was applied to ten real-world devices, identifying 254 unique flows, with over 27% only discovered through this new method. These insights enhance our understanding of device robustness, and the thus obtained profiles provide a more complete description of the network behavior of devices, as needed, for example, for the configuration of security solutions.},
groups = {International Conferences},
keywords = {IoT, Smart Home, networks, robustness, security, traffic profiling}
}
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