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Automated Privacy Positioning with Context-Awareness in Wearable Technology

Researchers will investigate attitudes toward wearables and sensors, enhance users’ awareness of their privacy risks, and design a  practical protection solution that provides users with the conveniences they expect while maintaining their privacy.

Funded by: CCI Northern Virginia Node

Rationale and Background

Wearable digital devices feature a rich set of advanced sensors to capture human physiological and activity data for user authentication, health-status tracking, activity monitoring, and sleep-quality evaluation. 

Use of these devices could also lead to privacy violations, as readings can reflect stress, emotion, cognitive status, and disease. Third-party apps on wearables are accessible by default, and wearables do not ask for user permission to remain activated. 

Because most users are unaware of these privacy issues, app developers and wearable manufacturers can collect users’ personal data without informing them. For example, one area of biometric vulnerability could be recording someone's gait and pairing this information with a GPS to localize and identify an individual.

These developments, coupled with the ubiquity of wearables, support the urgency for research on privacy violations and data leakage via sensors in wearables. 


The team will conduct research in four phases:

  • Measure users’ awareness of sensors in wearables and the data they collect. 
  • Facilitate users’ understanding of wearable privacy through experiential and educational intervention. 
  • Understand users’ needs for wearable privacy protection in general and for educational interventions.
  • Design a context-aware wearable privacy protection solution. 

Projected Outcomes

The project’s goals include:

  • An instrument quantifying users’ generic attitudes toward wearables and their privacy awareness of wearable sensors.
  • Secure prototypes tracking and computing user behavior and emotional status with wearable sensors.
  • A secure application supporting automatic context detection and sensor deactivation.
  • A secure user interface enabling users to view and potentially control status.     
  • A statistical report on the stated generic privacy attitudes and context-specific privacy attitudes from the individual wearable user study.
  • A prototype wearable with a signaling mechanism for sensor deactivation in specific contexts.