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Authors: Bethany K. Bracken 1 ; John Wolcott 2 ; Isaac Potoczny-Jones 2 ; Brittany A. Mosser 3 ; Isabell R. Griffith-Fillipo 3 and Patricia A. Arean 3

Affiliations: 1 Charles River Analytics, 625 Mount Auburn St., Cambridge, MA, U.S.A. ; 2 Tozny, LLC, 411 NW Park Ave. Ste 400, Portland, OR 97209, U.S.A. ; 3 Department of Psychiatry & Behavioral Sciences, University of Washington, 1959 NE Pacific Street, Seattle, WA, 98195, U.S.A.

Keyword(s): Remote Data Collection, Malicious Actors, Bots, Bad Actors.

Abstract: Although most human subjects research requires data collection by contacting local participants who visit a research site, some studies require increasingly large troves of data collected continuously during their typical daily lives using sensors (e.g., fitness trackers) and ecological momentary assessments. Long-term, continuous collection is becoming more feasible as smartphones become ubiquitous. To enable remote collection of these rich data sets while ensuring privacy, we built a system to allow secure and fully human-out-of-the-loop participant recruitment, screening, onboarding, data collection on smartphones, data transmission to the cloud, data security in the cloud, and data access by analysis and modeling teams. Study participants were paid for completion of daily ecological momentary assessments in keeping with standards of research equipoise, fairness, and retention strategies. However, our study attracted “malicious actors” who were pretending to be study participants, but were not, in order to receive payment. This opinion piece outlines how we initially detected malicious actors, and the steps we took in order to prevent future malicious actors from enrolling in the study. This resulted in several lessons learned that we think will be valuable for future studies that recruit, enroll, and maintain study participants remotely. (More)

CC BY-NC-ND 4.0

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Paper citation in several formats:
Bracken, B.; Wolcott, J.; Potoczny-Jones, I.; Mosser, B.; Griffith-Fillipo, I. and Arean, P. (2022). Detection and Remediation of Malicious Actors for Studies Involving Remote Data Collection. In Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2022) - HEALTHINF; ISBN 978-989-758-552-4; ISSN 2184-4305, SciTePress, pages 377-383. DOI: 10.5220/0010805500003123

@conference{healthinf22,
author={Bethany K. Bracken. and John Wolcott. and Isaac Potoczny{-}Jones. and Brittany A. Mosser. and Isabell R. Griffith{-}Fillipo. and Patricia A. Arean.},
title={Detection and Remediation of Malicious Actors for Studies Involving Remote Data Collection},
booktitle={Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2022) - HEALTHINF},
year={2022},
pages={377-383},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010805500003123},
isbn={978-989-758-552-4},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2022) - HEALTHINF
TI - Detection and Remediation of Malicious Actors for Studies Involving Remote Data Collection
SN - 978-989-758-552-4
IS - 2184-4305
AU - Bracken, B.
AU - Wolcott, J.
AU - Potoczny-Jones, I.
AU - Mosser, B.
AU - Griffith-Fillipo, I.
AU - Arean, P.
PY - 2022
SP - 377
EP - 383
DO - 10.5220/0010805500003123
PB - SciTePress