A Survey of Privacy Vulnerabilities of Mobile Device Sensors

TL;DR

This survey reviews how mobile device sensors can reveal sensitive personal data, discusses privacy risks, and evaluates methods to protect user privacy while maintaining data utility, highlighting open research challenges.

Contribution

It provides a comprehensive overview of privacy vulnerabilities in mobile sensors, summarizes privacy metrics and protection techniques, and identifies key open research questions.

Findings

Mobile sensors can infer demographics, health, and activity data.

Existing privacy metrics help quantify data sensitivity.

Privacy-preserving methods balance data utility and security.

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, emphasising critical aspects such as demographics, health and body features, activity and behaviour recognition, etc. 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 a represented for further advancements in the field.