Gameplay-Based Behavioral Fingerprinting for Stepped-Up Authentication
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Solution Overview
Problem
Existing user behavior fingerprint systems face challenges in establishing unique user profiles due to the need for multiple sessions to capture sufficient data, and they lack portability and consistency across different device types, making them ineffective for infrequent logins and varying form factors.
Innovation Solution
A gameplay-based method within a host application generates a user behavior fingerprint using interaction data such as taps, swipes, and typing, allowing for authentication within a single session and enhancing confidence in identity verification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional multi-session behavior fingerprinting is used, then sufficient user data can be captured, but the authentication process becomes time-consuming and impractical for infrequent logins
Solution Approach 1:
The system pre-generates a behavior fingerprint during the initial account setup process. This preliminary action captures sufficient user interaction data beforehand, eliminating the need for multiple authentication sessions later. The pre-captured fingerprint is stored and used for rapid verification during subsequent logins, resolving the contradiction between data sufficiency and authentication speed.
Solution Approach 2:
The authentication process is segmented into distinct phases: initial fingerprint generation during account setup, and rapid verification during authentication. This segmentation allows the system to perform comprehensive data collection once during setup, then use that stored information for quick subsequent verifications, addressing both the need for accurate profiles and fast authentication.
2Measurement precision
If device-specific behavior patterns are used, then authentication accuracy improves for that device, but portability across different device types is lost
Solution Approach 1:
The behavior fingerprinting system is designed to be device-agnostic and platform-independent. It captures universal human interaction patterns that transcend specific device types, making the authentication method universally applicable across smartphones, tablets, computers, and other form factors. This universality maintains authentication accuracy while enabling cross-device portability.
Solution Approach 2:
The system adapts its measurement parameters based on the device type being used. By dynamically adjusting which interaction metrics are collected and how they are weighted according to device capabilities, the system maintains consistent authentication accuracy across different platforms while preserving the ability to port fingerprints between devices.
3Ease of operation
If simple password authentication is used, then ease of access is maintained, but security against hacking and phishing attacks is insufficient
Solution Approach 1:
The behavior fingerprint acts as an intermediary verification layer between the user and the authentication system. Instead of relying solely on passwords that can be stolen through phishing, the system uses the fingerprint as a mediating factor that independently verifies user identity. This intermediary mechanism maintains ease of access while significantly enhancing security by adding a factor that is difficult to replicate or steal.
Solution Approach 2:
The system merges traditional password authentication with behavior fingerprint verification into a unified authentication process. This combination allows the system to maintain the simplicity of password entry while layering additional security through behavioral analysis. The merged approach provides both convenience and enhanced protection against hacking and phishing attacks.
Data Source
AI summary
A method may include receiving a login request from a computing device including authentication data for a user identifier; granting access to user identifier for a host application having a current level of authentication; receiving a request from the computing device to perform an action; determining the current level of authentication is less than an action level of authentication of the action; presenting a gaming application on the computing device embedded as part of the host application; monitoring telemetry data of the computing device during gameplay of the gaming application including: user interaction data associated with gaming application, and computing device movement data; calculating a current user behavior fingerprint using the telemetry data; calculating a fingerprint similarity score between the current user behavior fingerprint and a past user behavior fingerprint; determining the fingerprint similarity score is above a threshold similarity score; and based on the second determining, authorizing the action.