Haptic2FA: Haptics-Based Accessible Two-Factor Authentication for Blind and Low Vision People
Palavi V. Bhole, Ziming Li, Shivang Bokolia, Dr. Tae Oh, Dr. Garreth W. Tigwell, Dr. Roshan L. Peiris
School of Information,
Rochester Institute of Technology, Rochester, NY 14623, USA
Proceedings of the ACM on Human-Computer Interaction, Volume 8, Issue MHCI
Introduction
2FA and Accessibility Challenges for BLV Users
Two-Factor Authentication (2FA)
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A widely used security method for protecting online accounts.
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Combines "something you know" (e.g., password) with "something you have" (e.g., OTP).
Challenges for Blind and Low Vision (BLV) Users
Security
Traditional 2FA relies on visual cues, and screen readers can compromise security through shoulder surfing and eavesdropping.
Accessibility
These methods create barriers for visually impaired users, limiting access to secure online services.
Traditional 2FA and Accessibility Limitations
Traditional 2FA Methods
SMS codes, app-based authentication, hardware tokens and QR codes are widely used.
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Visual verification
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Text-based codes
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QR Codes
Accessibility Limitations
These methods rely on visual cues, posing challenges for BLV users.
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Visual impairments hinder code visibility
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Text-based codes can be difficult to read
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QR codes are inaccessible
Haptic2FA
an Accessible Solution
1
Haptic Patterns
Haptic2FA uses Morse code-like vibrations to convey authentication codes instead of OTPs for BLV users.
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Accessibility
This tactile feedback replaces visual cues, making authentication accessible for users with visual impairments.
3
Privacy and Security
Only the user feels the vibrations, mitigating shoulder-surfing and eavesdropping risks.
Haptic2FA Workflow
1
Login
The user initiates the login process on their smartphone.
2
Generate Haptic Pattern
The system generates a unique haptic pattern based on the user's credentials.
3
Feel Pattern
The user feels the vibrating haptic pattern through their smartphone or wearable.
4
Input Pattern
The user inputs the felt pattern using an input method.
Haptic2FA Workflow
Buttons
Select the pattern from multiple options.
Dot-Dash
Enter pattern via Dot and Dash buttons (like Morse code).
Gesture
Use taps/tap and holds to input the pattern.
Usability Study
Participants
10 BLV users (8 blind, 2 low vision), aged 26-45.
Testing
Each participant tested all three input methods.
Evaluated using two measures: Accuracy (correct pattern input) and Time (speed of entry).
Post-study interviews and NASA-TLX questionnaires to assess task load.
Feedback
Collected user feedback on accessibility and ease of use.
Study Results
Accuracy in Pattern Entry
93.3%
Buttons Method
94.4%
Dot-Dash Method
95.5%
Gesture Method
Average Time for Pattern Entry
14.4 seconds
Buttons Method
15.4 seconds
Dot-Dash Method
22.3 seconds
Gesture Method
User Feedback
Usability
Most participants found Haptic2FA easier to use and more independent compared to traditional 2FA.
Accessibility
Users found Haptic2FA accessible due to the use of tactile feedback.
Security
Participants felt more secure using haptic feedback in public places.
User Preferences and Suggestions
Pattern Length
Most participants Preferred 3-4 element haptic patterns for ease of memorization.
Input Method
Some users found the Gesture method slow but preferred it for security.
Suggestions
Participants suggested that pattern be received through notification but there should be a clear way to distinguish between other haptic feedbacks and the pattern haptics.
Conclusion and Future Work
Key Findings
Haptic2FA offers an accessible, secure alternative to traditional 2FA for BLV users. The study demonstrated its high accuracy and positive user feedback.
Future Work
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Explore cross-device authentication with wearables.
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Investigate complex haptic patterns for better security.
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Personalize vibration strength and speed for user preferences.
Takeaways
Haptic2FA reinforced the need for inclusive security design, ensuring 2FA is both secure and accessible. Balancing usability with security was a key challenge, requiring iterative design and user testing. This project highlighted how multi-sensory feedback can reduce accessibility barriers in authentication. Moving forward, I see potential for haptic feedback in broader cybersecurity applications, strengthening my commitment to equitable and user-centered design.