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Revamping Password Security: Leveraging Mnemonics for Enhanced Authentication
Hannah Ammah Serwaah Adjei1, Davide Giovanetti2, Miguel Vargas Martin1
1Ontario Tech University, Oshawa, Canada.
Summary
This study introduces a new security method that combines password manager data with user memory (mnemonics) to enhance digital authentication. This approach aims to improve security against password manager compromises with minimal impact on user experience.
Area of Science:
- Computer Science
- Human-Computer Interaction
- Cybersecurity
Background:
- Traditional password authentication faces challenges with increasing security demands and usability trade-offs.
- Password managers (PMs) improve usability but pose a significant risk if their vaults are compromised.
- Existing security enhancements often fail to balance robust protection with user-friendliness.
Purpose of the Study:
- To develop and evaluate a novel authentication system that augments passwords stored in password managers with a user-held secret.
- To enhance resilience against password manager vault compromise scenarios.
- To assess the feasibility and usability of mnemonic-based authentication in real-world login scenarios.
Main Methods:
- Developed Mindlock, a browser extension prototype acting as a mnemonic application interface.
- Combined password manager stored data with a user-remembered mnemonic for authentication.
- Used the stored password as a decoy to trigger alarms upon potential PM compromise.
- Conducted a user study to evaluate the system's feasibility and usability.
Main Results:
- Preliminary evidence suggests users can adopt mnemonic-based augmentation.
- The proposed method shows limited negative impact on usability during login routines.
- The decoy password mechanism can indicate potential password manager compromise.
Conclusions:
- Mnemonic-based augmentation offers a promising approach to enhance password security in the context of password manager usage.
- The system demonstrates potential for improving resilience against vault-only compromise attacks.
- Further research is needed to fully explore security implications under various threat models.
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