Usability Determines Safety for At-Risk Users: Evaluating Hidden Device Detectors for Intimate Partner Surveillance

DOI

This report contains the extended version of the paper accepted for presentation at the USENIX Symposium on Usable Privacy and Security (SOUPS) 2026. An abridged version of this work will be published in the conference proceedings.Hidden surveillance devices pose serious risks to survivors of intimate partner surveillance (IPS), yet consumer detection tools remain poorly understood from the user's perspective. Across in-room trials with 34 participants using 19 tools spanning eight interface types, we evaluated whether people can turn detector output into successful search, verification, and identification. Effectiveness depended on the actionability of feedback, not on sensing capability alone. Tools that presented a navigable list of detected devices with clear next steps outperformed signal-strength designs across every outcome, even when they sensed far less. Emotional impact proved equally consequential: false alarms heightened anxiety, and opaque failures led users to blame themselves. We offer design recommendations that treat detectors as 'decision-support' tools and propose reusable dimensions for evaluating them.

Identifier
DOI https://doi.org/10.5522/04/32660724.v1
Related Identifier HasPart https://ndownloader.figshare.com/files/65582064
Metadata Access https://api.figshare.com/v2/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=oai:figshare.com:article/32660724
Provenance
Creator Polamarasetty, Akhil; Tanczer, Leonie; Costanza, Enrico; Chetty, Kevin
Publisher University College London UCL
Contributor Figshare
Publication Year 2026
Rights https://creativecommons.org/licenses/by/4.0/; http://purl.org/coar/access_right/c_f1cf
OpenAccess true
Contact researchdatarepository(at)ucl.ac.uk
Representation
Language English
Resource Type Report
Discipline Other