Echoes of Privacy.
Uncovering the Profiling Practices of Voice Assistants
Tina Khezresmaeilzadeh (University of Southern California), Elaine Zhu (Northeastern University), Kiersten Grieco (Northeastern University), Daniel J. Dubois (Northeastern University), Konstantinos Psounis (University of Southern California), David Choffnes (Northeastern University)
Last updated: 07/28/2025
News
- 11/01/2024. This research has been accepted for publication at the 25th Privacy Enhancing Technologies Symposium (PETS2025) with the paper titled “Echoes of Privacy: Uncovering the Profiling Practices of Voice Assistants.“
Abstract
Many companies, including Google, Amazon, and Apple, offer voice assistants as a convenient solution for answering general voice queries and accessing their services. These voice assistants have gained popularity and can be easily accessed through various smart devices such as smartphones, smart speakers, smartwatches, and an increasing array of other devices. However, this convenience comes with potential privacy risks. For instance, while companies vaguely mention in their privacy policies that they may use voice interactions for user profiling, it remains unclear to what extent this profiling occurs and whether voice interactions pose greater privacy risks compared to other interaction modalities.
In this paper, we conduct 1,171 experiments involving 24,530 queries with different personas and interaction modalities during 20 months to characterize how the three most popular voice assistants profile their users. We analyze factors such as labels assigned to users, their accuracy, the time taken to assign these labels, differences between voice and web interactions, and the effectiveness of profiling remediation tools offered by each voice assistant. Our findings reveal that profiling can happen without interaction, can be incorrect and inconsistent at times, may take several days or weeks to change, and is affected by the interaction modality.
About this publication
Our research has been published in the proceedings of the 25th Privacy Enhancing Technologies Symposium (PETS 2025).
Paper title: Echoes of Privacy: Uncovering the Profiling Practices of Voice Assistants
Authors: Tina Khezresmaeilzadeh (University of Southern California), Elaine Zhu (Northeastern University), Kiersten Grieco (Northeastern University), Daniel J. Dubois (Northeastern University), Konstantinos Psounis (University of Southern California), David Choffnes (Northeastern University)
Full Text (PDF): available.
Software and data: available on Github.
Presentation: will be added after the symposium.
Citation:
@inproceedings{khezresmaeilzadeh-pets25,
title={{Echoes of Privacy: Uncovering the Profiling Practices of Voice Assistants}},
author={Khezresmaeilzadeh, Tina and Zhu, Elaine and Grieco, Kiersten and Dubois, Daniel J. and Psounis, Konstantinos and Choffnes, David},
booktitle={Proc. of the Privacy Enhancing Technologies Symposium (PETS)},
year={2025}
}
Acknowledgments
- This research was partially supported by:
- NSF ProperData Frontier award (SaTC-1955227, SaTC-1956435).
- Consumer Reports Innovation Lab.
- We thank the reviewers for their valuable feedback and Ganesh Danke, Shriya Dhaundiya, Akshata Lolayekar, Tilak Patel, Sairam Ramasubramanian, Shantanu Sachdeva, Landyn Sparacino, and Kaveh Waddell for their contributions.