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dc.contributor.authorGirish, Aniketh 
dc.contributor.authorTapiador, Juan
dc.contributor.authorMatic, Srdjan 
dc.contributor.authorVallina-Rodriguez, Narseo 
dc.date.accessioned2022-10-13T07:35:24Z
dc.date.available2022-10-13T07:35:24Z
dc.date.issued2022-10
dc.identifier.urihttps://hdl.handle.net/20.500.12761/1627
dc.description.abstractThe 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.es
dc.description.sponsorshipODIOes
dc.description.sponsorshipTrustAwarees
dc.language.isoenges
dc.titleTowards an extensible privacy analysis framework for Smart Homeses
dc.typeconference objectes
dc.conference.date25-27 October 2022es
dc.conference.placeNice, Francees
dc.conference.titleInternet Measurement Conference*
dc.event.typeconferencees
dc.pres.typeposteres
dc.rights.accessRightsopen accesses
dc.acronymIMC*
dc.rankA*
dc.description.refereedTRUEes
dc.description.statuspubes


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