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Towards an extensible privacy analysis framework for Smart Homes

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dspace_version_imc22.pdf (809.7Kb)
Identificadores
URI: https://hdl.handle.net/20.500.12761/1627
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Autor(es)
Girish, Aniketh; Tapiador, Juan; Matic, Srdjan; Vallina-Rodriguez, Narseo
Fecha
2022-10
Resumen
The IoT ecosystem is an intricate and complex network of stake- holders that includes platforms, developers, ad networks and cloud providers. However, the ability of smart home platforms and devices to interact and exchange data, together with the data-driven busi- ness models adopted by most IoT stakeholders open the ground for unknown and unexpected privacy risks. Existing black-box testing approaches to audit IoT platforms cannot identify data dissemina- tion through side- and covert-channels, and for this reason they are not well suited for rich execution environments where a wide range of devices and applications can co-operate using multiple network protocols and interfaces. This poster proposes ImposTer, a cost-effective and extensible privacy framework for exhaustively testing the IoT ecosystem. Our framework is able to capture, model and emulate horizontal interactions that occur across the different devices in a consumer household.
Compartir
Ficheros
dspace_version_imc22.pdf (809.7Kb)
Identificadores
URI: https://hdl.handle.net/20.500.12761/1627
Metadatos
Mostrar el registro completo del ítem

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