mlsanityData to 7 Oct 2026

"I'm not for sale" -- Perceptions and limited awareness of privacy risks by digital natives about location data

arXiv 2502.11658 ↗First posted 17 Feb 2025cs.CY cs.AI cs.CRcited by 0

Not on the map. Why?

Abstract (arXiv)

Although mobile devices benefit users in their daily lives in numerous ways, they also raise several privacy concerns. For instance, they can reveal sensitive information that can be inferred from location data. This location data is shared through service providers as well as mobile applications. Understanding how and with whom users share their location data -- as well as users' perception of the underlying privacy risks --, are important notions to grasp in order to design usable privacy-enhancing technologies. In this work, we perform a quantitative and qualitative analysis of smartphone users' awareness, perception and self-reported behavior towards location data-sharing through a survey of n=99 young adult participants (i.e., digital natives). We compare stated practices with actual behaviors to better understand their mental models, and survey participants' understanding of privacy risks before and after the inspection of location traces and the information that can be inferred therefrom. Our empirical results show that participants have risky privacy practices: about 54% of participants underestimate the number of mobile applications to which they have granted access to their data, and 33% forget or do not think of revoking access to their data. Also, by using a demonstrator to perform inferences from location data, we observe that slightly more than half of participants (57%) are surprised by the extent of potentially inferred information, and that 47% intend to reduce access to their data via permissions as a result of using the demonstrator. Last, a majority of participants have little knowledge of the tools to better protect themselves, but are nonetheless willing to follow suggestions to improve privacy (51%). Educating people, including digital natives, about privacy risks through transparency tools seems a promising approach.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 5 of its 104 references that are in the map. First posted on arXiv 17 Feb 2025.

Builds on

5 of 104 references.

References · 5

  1. 2018Datasheets for Datasetscited by 1,371
  2. 2015Android Permissions Remystified: A Field Study on Contextual Integritycited by 15
  3. 2018The Long Road to Computational Location Privacy: A Surveycited by 10
  4. 2021Are Privacy Dashboards Good for End Users? Evaluating User Perceptions and Reactions to Google's My Activity (Extended Version)cited by 2
  5. 2014An Automated Social Graph De-anonymization Techniquecited by 1

Built on by

Not cited yet.