skip to main content
10.1145/3170427.3188510acmconferencesArticle/Chapter ViewAbstractPublication PageschiConference Proceedingsconference-collections
abstract
Public Access

Concern But No Action: Consumers' Reactions to the Equifax Data Breach

Published:20 April 2018Publication History

ABSTRACT

Following the 2017 Equifax data breach, we conducted four preliminary interviews to investigate how consumers view credit bureaus and the information flows around these agencies, what they perceive as risks of the Equifax breach, and how they reacted in practice. We found that although participants could properly articulate the purpose of credit bureaus, their understanding of credit bureaus' data collection practices was divided and incomplete. Although most of them conceptualized identity theft as the primary risk of data breaches disclosing credit information, and noted a lack of trust/self-efficacy in controlling their data collected by credit bureaus, they did not take sufficient protective actions to deal with the perceived risks. Our findings provide implications for the design of future security-enhancing tools regarding credit data, education and public policy, with the aim to empower consumers to better manage their sensitive data and protect themselves from future data breaches.

References

  1. Ben Berliner. 2017. Equifax breach drives legislative push on data privacy. (2017). https://fcw.com/articles/2017/10/23/databreach-legislation-berliner.aspx.Google ScholarGoogle Scholar
  2. Cristian Bravo-Lillo, Lorrie Faith Cranor, Julie Downs, and Saranga Komanduri. 2011. Bridging the gap in computer security warnings: A mental model approach. IEEE Security &Privacy 9, 2 (2011), 18--26. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. L. Jean Camp. 2009. Mental models of privacy and security. IEEE Technology and Society Magazine 28, 3 (2009).Google ScholarGoogle ScholarCross RefCross Ref
  4. Federal Trade Commission. 2017. The Equifax Data Breach. (2017). https://www.ftc.gov/equifax-data-breach.Google ScholarGoogle Scholar
  5. Ponemon Institute. 2014. The Aftermath of a Data Breach: Consumer Sentiment. Technical Report. https://www.ponemon.org/local/upload/file/Consumer%20Study%20on%20Aftermath%20of%20a%20Breach%20FINAL%202.pdf.Google ScholarGoogle Scholar
  6. Iulia Ion, Rob Reeder, and Sunny Consolvo. 2015. "... No one Can Hack My Mind" Comparing Expert and Non-Expert Security Practices.. In SOUPS, Vol. 15. 1--20.Google ScholarGoogle Scholar
  7. Ruogu Kang, Laura Dabbish, Nathaniel Fruchter, and Sara Kiesler. 2015. My data just goes everywhere: user mental models of the internet and implications for privacy and security. In Proc. of the 11th Symposium On Usable Privacy and Security (SOUPS). 39--52.Google ScholarGoogle Scholar
  8. Spyros Kokolakis. 2017. Privacy attitudes and privacy behaviour: A review of current research on the privacy paradox phenomenon. Computers &Security 64 (2017), 122--134. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Annamaria Lusardi and Olivia S. Mitchelli. 2007. Financial literacy and retirement preparedness: Evidence and implications for financial education. Business economics 42, 1 (2007), 35--44.Google ScholarGoogle Scholar
  10. Maureen Mahoney. 2014. Errors and Gotchas: How Credit Report Errors and Unreliable Credit Scores Hurt Consumers. Technical Report. http://consumersunion.org/wp-content/uploads/2014/04/Errors-and-Gotchas-report.pdf.Google ScholarGoogle Scholar
  11. Lennart Sjöberg. 2000. Factors in risk perception. Risk analysis 20, 1 (2000), 1--12.Google ScholarGoogle Scholar
  12. Rick Wash. 2010. Folk models of home computer security. In Proc. of the 6th Symposium on Usable Privacy and Security. ACM, 11. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Suzanne Woolley. 2017. Few Americans Are Freezing Their Credit After the Equifax Hack. (2017). https://www.bloomberg.com/news/articles/201710-06/few-americans-are-freezing-their-creditafter-the-equifax-hack.Google ScholarGoogle Scholar
  14. Yaxing Yao, Davide Lo Re, and Yang Wang. 2017. Folk Models of Online Behavioral Advertising. In Proc. of the 2017 ACM Conf. on Computer Supported Cooperative Work and Social Computing (CSCW). 1957--1969. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. Concern But No Action: Consumers' Reactions to the Equifax Data Breach

      Recommendations

      Comments

      Login options

      Check if you have access through your login credentials or your institution to get full access on this article.

      Sign in
      • Published in

        cover image ACM Conferences
        CHI EA '18: Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems
        April 2018
        3155 pages
        ISBN:9781450356213
        DOI:10.1145/3170427

        Copyright © 2018 Owner/Author

        Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 20 April 2018

        Check for updates

        Qualifiers

        • abstract

        Acceptance Rates

        CHI EA '18 Paper Acceptance Rate1,208of3,955submissions,31%Overall Acceptance Rate6,164of23,696submissions,26%

        Upcoming Conference

        CHI '24
        CHI Conference on Human Factors in Computing Systems
        May 11 - 16, 2024
        Honolulu , HI , USA

      PDF Format

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader