Behavioral Pattern Authentication for Mobile Devices
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current authentication methods, whether knowledge-based or biometric, face challenges such as user forgetfulness, ease of compromise, or high costs associated with specialized equipment, necessitating a more reliable and cost-effective approach.
Innovation Solution
Defining an expected pattern of device usage for authorized users based on historical actions, comparing observed usage to this pattern, and requiring authentication when deviations exceed a threshold, with partial or complete device disabling if unauthorized.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If biometric-based authentication is used, then authentication reliability is improved, but device complexity and cost increase due to specialized equipment requirements
Solution Approach 1:
The patent creates a digital copy of the user's behavioral pattern (usage profile) rather than requiring physical biometric characteristics. This behavioral template is generated by monitoring and analyzing the user's historical device usage patterns, creating a replicable digital representation that can be used for authentication without specialized hardware.
Solution Approach 2:
The patent replaces mechanical/biometric authentication systems with a software-based behavioral analysis system. Instead of using fingerprints, facial recognition, or other physical biometrics that require specialized scanners and sensors, the system uses software to monitor, analyze, and compare usage patterns, substituting physical measurement mechanisms with digital data processing.
2Device complexity
If knowledge-based authentication (passwords) is used, then device complexity is reduced, but authentication security deteriorates due to ease of compromise and user forgetfulness
Solution Approach 1:
The system automatically monitors, analyzes, and updates the user's behavioral pattern without requiring manual input or configuration. The authentication process serves itself by continuously learning from usage data and automatically comparing observed behavior against the established profile, eliminating the need for users to manage passwords or provide biometric samples manually.
Solution Approach 2:
The system continuously monitors actual device usage and compares it against the established behavioral pattern, providing feedback to detect deviations. This ongoing feedback loop allows the system to adapt to legitimate changes in usage patterns while detecting unauthorized access attempts, creating a dynamic authentication mechanism that improves over time.
3Reliability
If behavioral pattern monitoring is implemented, then authentication security is improved without specialized equipment, but processing requirements and computational complexity increase
Solution Approach 1:
The system performs preliminary analysis of usage patterns during normal device operation, building and refining the behavioral profile in advance. By continuously learning and storing the expected behavior patterns during legitimate usage, the system prepares authentication data structures that can be quickly compared against future observations, reducing real-time processing requirements during actual authentication events.
Data Source
AI summary
A method for authentication is disclosed. During use, the observed usage of the device is compared to an expected pattern of usage of the device. Deviation between the observed and expected usage indicates that the user might not be authorized to use the device. If the deviation exceeds a threshold, a credential is required from the user to authenticate itself as the authorized user.