Mostrar el registro sencillo del ítem

dc.contributor.authorPradeep, Amogh
dc.contributor.authorFeal, Álvaro 
dc.contributor.authorGamba, Julien 
dc.contributor.authorRao, Ashwin
dc.contributor.authorLindorfer, Martina
dc.contributor.authorVallina-Rodriguez, Narseo 
dc.contributor.authorChoffnes, David
dc.date.accessioned2022-10-07T09:28:20Z
dc.date.available2022-10-07T09:28:20Z
dc.date.issued2023-07
dc.identifier.urihttps://hdl.handle.net/20.500.12761/1622
dc.description.abstractThe privacy-related behavior of mobile browsers has remained widely unexplored by the research community. In fact, as opposed to regular Android apps, mobile browsers may present contradicting privacy behaviors. On the one hand, they can have access to (and can expose) a unique combination of sensitive user data, from users' browsing history to permission-protected personally identifiable information (PII) such as unique identifiers and geolocation. On the other hand, they are in a unique position to protect users' privacy by limiting data sharing with other parties by implementing ad-blocking features. In this paper, we perform a comparative and empirical analysis on how hundreds of Android web browsers protect or expose user data during browsing sessions. To this end, we collect the largest dataset of Android browsers to date, from the Google Play Store and four Chinese app stores. Then, we develop a novel analysis pipeline that combines static and dynamic analysis methods to find a wide range of privacy-enhancing (e.g., ad-blocking) and privacy-harming behaviors (e.g., sending browsing histories to third parties, not validating TLS certificates, and exposing PII---including non-resettable identifiers---to third parties) across browsers. We find that various popular apps on both Google Play and Chinese stores have these privacy-harming behaviors, including apps that claim to be privacy-enhancing in their descriptions. Overall, our study not only provides new insights into important yet overlooked considerations for browsers' adoption and transparency, but also that automatic app analysis systems (e.g., sandboxes) need context-specific analysis to reveal such privacy behaviors.es
dc.language.isoenges
dc.titleNot Your Average App: A Large-scale Privacy Analysis of Android Browserses
dc.typeconference objectes
dc.conference.placeLaussane, Switzerlandes
dc.conference.titlePrivacy Enhancing Technologies Symposium (was International Workshop of Privacy Enhancing Technologies)*
dc.event.typeconferencees
dc.pres.typepaperes
dc.rights.accessRightsopen accesses
dc.acronymPETS*
dc.rankA*
dc.relation.projectNameTrustawarees
dc.relation.projectNameOdioes
dc.relation.projectNameRamon y Cajal (Narseo Vallina-Rodriguez)es
dc.description.refereedTRUEes
dc.description.statusinpresses


Ficheros en el ítem

FicherosTamañoFormatoVer

No hay ficheros asociados a este ítem.

Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem