Evaluating Privacy and Usability Trade-offs in Decentralized Identity Systems

Roshan Kumar Chaudhary

Abstract


As decentralized identity systems gain momentum in reshaping digital authentication, a critical challenge emerges: how to balance privacy preservation with usability. This study evaluates two identity management models: a traditional centralized login system and a decentralized identity (DID) framework based on blockchain technologies. We implement and simulate core functions such as credential issuance, selective disclosure, and verification using existing tools like Self.ID and MetaMask. Through a structured usability test involving 12 participants, we collect both quantitative and qualitative data, analyzing metrics such as task completion time, error rate, user satisfaction, and perceived control over data. Findings reveal that while decentralized systems significantly reduce data exposure (with an average of 68% less personal data shared), they introduce usability barriers. Users took 41% longer to complete tasks and reported lower confidence levels. These results highlight the need for improved onboarding strategies and user-centric design to bridge the privacy–usability divide. This research contributes empirical evidence to support the development of ethical and accessible digital identity infrastructures.

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References


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