Browser Fingerprint Authentication for E-Commerce Login
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Solution Overview
Problem
E-commerce platforms face challenges in efficiently authenticating users during browsing sessions, leading to delayed purchases and forgotten credentials, as users often need to manually log in, disrupting the shopping experience.
Innovation Solution
The system receives unique fingerprint information from unauthenticated browsing sessions and compares it with historical data to identify matching user accounts with a threshold confidence level, allowing for automatic authentication without requiring login credentials through associated devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual login credentials are required for user authentication, then security is maintained, but user experience deteriorates due to delays and forgotten credentials
Solution Approach 1:
The system performs preliminary actions by collecting device fingerprint information (browser type, version, language, platform, screen resolution, timezone, etc.) during the browsing session before authentication is required. This pre-collected data is stored and later used to automatically identify and authenticate the user, eliminating the need for manual credential entry and reducing authentication time while maintaining security.
2Productivity
If automatic authentication via fingerprint matching is implemented, then authentication speed improves, but system complexity increases due to fingerprint collection and comparison mechanisms
Solution Approach 1:
The system uses universally available device and browser attributes (browser type, version, language, platform, screen resolution, timezone, etc.) that already exist in every user's browsing environment to create a fingerprint. This approach avoids adding complex hardware or software components, as the authentication mechanism leverages data that is naturally present during normal browsing, thereby improving efficiency without significantly increasing system complexity.
3Extent of automation
If fingerprint information is collected during browsing, then automatic authentication becomes possible, but user privacy concerns increase due to data collection
Solution Approach 1:
The system uses the user's own device characteristics and browsing environment as an intermediary identifier rather than collecting personal information. The fingerprint is derived from anonymous, non-personal attributes of the browsing session (browser configuration, device properties, etc.) that do not directly identify the user but uniquely identify the browsing instance, thereby enabling automation while minimizing privacy impact.
Data Source
AI summary
Methods and systems for user authentication. At a server, receiving unique fingerprint information for an unauthenticated browsing session with the server by a first user device. The unique fingerprint information received is compared with respective historical fingerprint information associated with a plurality of user accounts stored on the server. Based on the comparison, determining that one of the plurality of user accounts has associated historical fingerprint information that matches the unique fingerprint information with at least a threshold confidence level. In response to receiving user input from a second device indicating that the unauthenticated browsing session corresponds to the one of the plurality of user accounts, associating the unauthenticated browsing session with the one of the plurality of user accounts.