User Identity Detection via Behavioral Activity Patterns
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Solution Overview
Problem
Existing methods for identifying electronic device users are inconvenient, as users often struggle to remember passwords or PINs, and biometric measures require additional equipment, making them impractical for secure and personalized device customization.
Innovation Solution
A user identification system that monitors and compares the user's activity patterns, including content selection, input methods, and context, to identify users by detecting idiosyncratic patterns and updating profiles based on user behavior, allowing for secure and personalized device customization without the need for additional equipment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If password or PIN is used for user identification, then security is improved, but ease of operation deteriorates because users find it inconvenient to remember passwords or PINs
Solution Approach 1:
The system automatically monitors and learns user activity patterns without requiring users to manually provide identification information. The identification module continuously collects data about user interactions with the electronic device, automatically builds profiles, and performs authentication without user intervention, thereby eliminating the need for users to remember passwords or PINs while maintaining security
Solution Approach 2:
The patent replaces the mechanical/memory-based authentication system (passwords, PINs that require human recall) with an automated pattern recognition system that analyzes behavioral data. The identification module uses software algorithms to monitor, compare, and recognize unique activity patterns, substituting the need for human memory with automated computational analysis
2Reliability
If biometric parameter measurement is used for user identification, then security is improved, but device complexity deteriorates because additional equipment is required
Solution Approach 1:
The identification module serves multiple functions using a single integrated system: it monitors user activity patterns, compares patterns against stored profiles, authenticates users, and updates profiles automatically. This multi-functional approach eliminates the need for separate biometric hardware while providing secure identification and customization capabilities
Solution Approach 2:
The system performs self-contained user identification using only the electronic device's existing processing capabilities and input interfaces. The identification module automatically collects, analyzes, and stores activity pattern data without requiring external biometric equipment, making the device self-sufficient for secure authentication
Data Source
AI summary
Methods and apparatuses for determining the identity of the user detect a current user's electronic device activity pattern; compare the detected activity pattern against a plurality of user action identification profiles, wherein each user action identification profile is associated with a particular user; and use the comparing to identify the current user as being the particular user.