Use & Abuse of Personal Information, Part II: Robust Generation of Fake IDs for Privacy Experimentation

When personal information is shared across the Internet, we have limited confidence that the designated second party will safeguard it as we would prefer. Privacy policies offer insight into the best practices and intent of the organization, yet most are written so loosely that sharing with undefined third parties is to be anticipated. Tracking these sharing behaviors and identifying the source of unwanted content is exceedingly difficult when personal information is shared with multiple such second parties. This paper formulates a model for realistic fake identities, constructs a robust fake identity generator, and outlines management methods targeted towards online transactions (email, phone, text) that pass both cursory machine and human examination for use in personal privacy experimentation. This fake ID generator, combined with a custom account signup engine, are the core front-end components of our larger Use and Abuse of Personal Information system that performs one-time transactions that, similar to a cryptographic one-time pad, ensure that we can attribute the sharing back to the single one-time transaction and/or specific second party. The flexibility and richness of the fake IDs also serve as a foundational set of control variables for a wide range of social science research questions revolving around personal information. Collectively, these fake identity models address multiple inter-disciplinary areas of common interest and serve as a foundation for eliciting and quantifying personal information-sharing behaviors.

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Institutions

Publication Details

Journal
Journal of Cybersecurity and Privacy
Published
2024-08-11
DOI
https://doi.org/10.3390/jcp4030026
Citations
4
Primary Topic
User Authentication and Security Systems
Type
article
Field-Weighted Citation Impact
3.12

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article

Use & Abuse of Personal Information, Part II: Robust Generation of Fake IDs for Privacy Experimentation

Alan J. Michaels, Christopher Henshaw, Madison G. Boswell, Jack Kolenbrander et al.
4 citations
Journal of Cybersecurity and Privacy
User Authentication and Security Systems
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article

Use & Abuse of Personal Information, Part II: Robust Generation of Fake IDs for Privacy Experimentation

Alan J. Michaels, Christopher Henshaw, Madison G. Boswell, Jack Kolenbrander, Elliott Rheault, Ethan Husmann
article en
4 citations

Abstract

When personal information is shared across the Internet, we have limited confidence that the designated second party will safeguard it as we would prefer. Privacy policies offer insight into the best practices and intent of the organization, yet most are written so loosely that sharing with undefined third parties is to be anticipated. Tracking these sharing behaviors and identifying the source of unwanted content is exceedingly difficult when personal information is shared with multiple such second parties. This paper formulates a model for realistic fake identities, constructs a robust fake identity generator, and outlines management methods targeted towards online transactions (email, phone, text) that pass both cursory machine and human examination for use in personal privacy experimentation. This fake ID generator, combined with a custom account signup engine, are the core front-end components of our larger Use and Abuse of Personal Information system that performs one-time transactions that, similar to a cryptographic one-time pad, ensure that we can attribute the sharing back to the single one-time transaction and/or specific second party. The flexibility and richness of the fake IDs also serve as a foundational set of control variables for a wide range of social science research questions revolving around personal information. Collectively, these fake identity models address multiple inter-disciplinary areas of common interest and serve as a foundation for eliciting and quantifying personal information-sharing behaviors.

Journal of Cybersecurity and PrivacyVol. 4(3)
Virginia Tech (US)
National Science Foundation, Raytheon Technologies
Peace, Justice and strong institutions
Openalex Percentile: Top 7%
User Authentication and Security Systems
3.12
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