Behavioral Biometric Authentication via Unconscious Interaction Analysis
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Solution Overview
Problem
Existing methods for distinguishing human behavior from machine behavior in device interactions require conscious user responses, which can be boring and inefficient, and lack the ability to utilize sensor data effectively.
Innovation Solution
A method that collects and evaluates data on unconscious user behavior, using biological and physical parameters to differentiate between human and machine interactions through a fuzzy validation process, without requiring conscious user responses, by analyzing input data from devices such as keyboards and sensors to identify human-like or machine-like behavior.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If challenge-response tests (CAPTCHA) are used to distinguish human from machine behavior, then security against machine automation is improved, but user convenience deteriorates due to requiring conscious user responses
Solution Approach 1:
The system collects behavioral data from users during normal interactions with the service before any security challenge is needed. This preliminary data collection establishes a baseline of human-like behavior patterns (typing rhythm, mouse movements, scrolling behavior) that can be used for automatic authentication without requiring users to complete CAPTCHA challenges, thereby maintaining security while preserving user convenience
Solution Approach 2:
The system performs automatic behavior analysis and authentication without requiring user intervention. The behavioral biometric algorithms automatically process collected interaction data, compare it against machine-like behavior patterns, and make authentication decisions in the background, eliminating the need for users to consciously respond to security challenges
2Ease of operation
If behavioral data collection is performed in the background without user awareness, then user convenience is improved, but measurement precision may worsen due to limited data availability
Solution Approach 1:
The system collects multiple types of interaction data simultaneously (keyboard input timing, mouse movement patterns, scrolling behavior, form filling patterns) that serve both the primary function of providing service to the user and the secondary function of gathering behavioral biometric data for authentication. This multi-functional approach ensures sufficient data quantity and variety for accurate behavioral analysis while maintaining seamless user experience
Solution Approach 2:
The system continuously monitors behavioral patterns and provides feedback by adjusting the stringency of security checks based on observed behavior. When human-like behavior is detected, the system may reduce or eliminate security challenges; when suspicious patterns emerge, it can trigger additional verification, thereby maintaining measurement precision while adapting to user convenience needs
Data Source
AI summary
A computer-implemented method, computer program product, and system for determining whether a user exhibits machine behavior, or does not exhibit human-like behavior, thereby to authenticate the user for access to a software service.