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A Survey of Privacy Vulnerabilities of Mobile Device Sensors

Paula Delgado-Santos, Giuseppe Stragapede, Rubén Tolosana, Richard Guest, Farzin Deravi, Rubén Vera-Rodríguez

2022ACM Computing Surveys66 citationsDOIOpen Access PDF

Abstract

The number of mobile devices, such as smartphones and smartwatches, is relentlessly increasing, to almost 6.8 billion by 2022, and along with it, the amount of personal and sensitive data captured by them. This survey overviews the state of the art of what personal and sensitive user attributes can be extracted from mobile device sensors, emphasizing critical aspects such as demographics, health and body features, activity and behavior recognition, and so forth. In addition, we review popular metrics in the literature to quantify the degree of privacy and discuss powerful privacy methods to protect the sensitive data while preserving data utility for analysis. Finally, open research questions are presented for further advancements in the field.

Topics & Concepts

Computer scienceMobile deviceSmartwatchDemographicsField (mathematics)Internet privacyPersonally identifiable informationComputer securityInformation privacyHuman–computer interactionData scienceWorld Wide WebWearable computerEmbedded systemMathematicsSociologyPure mathematicsDemographyPrivacy-Preserving Technologies in DataPrivacy, Security, and Data ProtectionMobile Crowdsensing and Crowdsourcing
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