Privacy‑Preserving Behavioral Biometrics for Seamless Banking UX

  • Authors

    • David Thompson Vice President Operations, Global Solutions LLC, USA. Author
    • Jennifer Clark Senior Data Scientist, Innovate Analytics, USA. Author

    DOI:

    https://doi.org/10.67228/3071561X/IJIRHT-2022PII1Q8D

    Published 09-05-2022

  • Behavioral Biometrics, Privacy-Preserving Machine Learning, Digital Banking, User Experience (UX), Federated Learning, Differential Privacy, Biometric Authentication, Secure FinTech, Seamless Authentication, Regulatory Compliance

    Issue

    Vol. 5 No. 2 (2022)

    Section

    Articles

    How to Cite

    [1]
    D. Thompson and J. Clark, “Privacy‑Preserving Behavioral Biometrics for Seamless Banking UX”, IJIRHT, vol. 5, no. 2, pp. 01–12, Sep. 2022, doi: 10.67228/3071561X/IJIRHT-2022PII1Q8D.

  • Abstract

    As digital banking becomes the norm, the demand for authentication mechanisms that are both secure and seamless is growing. Behavioral biometrics—such as typing patterns, mouse dynamics, and gesture recognition—offer a passive and continuous method of user authentication without disrupting the user experience. However, these biometrics raise significant privacy concerns due to their sensitivity and the potential for misuse. This paper explores the integration of privacy-preserving techniques with behavioral biometric systems to enable secure, transparent, and user-friendly banking experiences. We analyze various privacy-preserving technologies, propose an architecture tailored for financial applications, and discuss the trade-offs between usability, accuracy, and privacy. Our findings show that with careful design, behavioral biometrics can enhance banking UX while adhering to modern privacy standards.

  • References

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