Behavioral Profiling for Adaptive Authentication
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Solution Overview
Problem
Existing authentication systems rely on static measures such as passwords, PINs, and biometrics, which can be easily circumvented and lack flexibility to adapt to changing user behavior, thereby compromising security and convenience.
Innovation Solution
A behavioral profiling method and system that identifies and compares user behavioral characteristics during device operation to a pre-developed behavioral profile, determining an appropriate mark difficulty level and prompting the user to draw a mark as part of the login process, thereby enhancing authentication security without sacrificing ease of use.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional static authentication measures (passwords, PINs, biometrics) are used, then ease of operation is maintained, but security reliability deteriorates because these measures can be easily circumvented and counterfeited
Solution Approach 1:
The patent transitions from static authentication (fixed passwords/biometrics) to dynamic authentication by continuously monitoring behavioral characteristics during device operation. The system adapts authentication requirements in real-time based on detected behavioral patterns, making the authentication process both more secure and context-aware while maintaining user convenience through automated behavioral analysis.
Solution Approach 2:
The system implements feedback by comparing real-time behavioral characteristics against stored behavioral profiles and using this comparison to dynamically adjust authentication decisions. The behavioral profile is continuously updated based on observed user behavior, creating a self-learning system that improves security while adapting to legitimate user patterns.
2Reliability
If more identifying information is collected to improve authentication confidence, then security reliability improves, but device complexity and user burden increase
Solution Approach 1:
The system performs self-service by automatically collecting, analyzing, and storing behavioral characteristics without requiring explicit user input or manual configuration. The behavioral profiling occurs passively during normal device operation, eliminating the need for users to provide additional identifying information while maintaining high authentication confidence through automated pattern recognition.
Solution Approach 2:
The patent replaces traditional mechanical authentication systems (physical security tokens, manual password entry) with a software-based behavioral analysis system. This substitution uses computational methods to monitor and analyze device operation patterns, reducing physical complexity while enhancing authentication reliability through sophisticated algorithmic processing of behavioral data.
3Adaptability or versatility
If static authentication measures are used, then ease of operation is maintained, but adaptability to changing user behavior deteriorates
Solution Approach 1:
The system dynamically adapts to changing user behavior by continuously updating behavioral profiles based on observed patterns during device operation. Rather than relying on fixed authentication criteria, the system adjusts its understanding of legitimate user behavior in real-time, maintaining both adaptability and operational simplicity through automated behavioral learning.
Solution Approach 2:
The system performs preliminary action by establishing behavioral profiles during normal device operation before authentication events occur. This proactive behavioral characterization allows the system to quickly and simply authenticate users by comparing their behavior against pre-established patterns, eliminating the need for complex real-time analysis while maintaining high adaptability to user behavior changes.
Data Source
AI summary
A computer-implemented method includes identifying behavioral characteristics of a user related to operation of a computing device prior to an online account session. The method includes comparing the behavioral characteristics to a behavioral profile previously developed based on prior behavioral characteristics of the user, and determining an appropriate mark difficulty level based on a variation between the behavioral characteristics and the behavioral profile. The method includes selecting, from a plurality of prompts stored in a prompt database, a prompt that comprises instructions to draw a mark having the appropriate mark difficulty level, where other prompts of the plurality of prompts comprise instructions to draw other marks different from the mark, and providing the prompt to the user as part of a logon process for the online account session.


