Generative AI Image Authentication for User Activity Verification
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current authentication methods are inadequate for integrating local Large Language Models (LLMs) into multi-modal authentication systems, particularly for users with disabilities and in industrial or hostile environments, where traditional methods are unsatisfactory and vulnerable to exploits.
Innovation Solution
A system and method for secure user authentication using generative Artificial Intelligence (AI) to create random image questions based on recent user-activity and location data across communication platforms, incorporating DALL-E and GPT-4V components for image generation and text processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional authentication methods are used, then ease of operation is maintained, but security and adaptability to diverse user needs deteriorate
Solution Approach 1:
The authentication system dynamically adapts its modality requirements based on user profile and environmental context. The system determines which modalities (visual, auditory, tactile) are appropriate for each authentication instance, making the authentication process flexible rather than static. This resolves the contradiction by allowing the system to maintain security through adaptive challenge selection while adjusting operational complexity based on user needs.
Solution Approach 2:
The system changes parameters such as authentication modality, challenge type, and verification criteria based on user characteristics and environmental factors. For example, it may switch from visual image recognition to auditory or tactile modalities for users with visual impairments, or adjust the complexity of challenges based on the detected environment. This parameter adaptation maintains security while accommodating diverse operational needs.
2Power
If cloud-based AI processing is used, then computational performance is improved, but privacy concerns increase
Solution Approach 1:
The authentication system segments the processing workflow between client device and cloud server. The client device collects biometric data and performs initial processing locally, then transmits only essential authentication challenges and verification results to the cloud. This segmentation reduces privacy risks by minimizing cloud exposure of sensitive biometric data while still leveraging cloud computational resources for complex AI processing when needed.
Data Source
Figure 1A
Figure 1B
Figure 2
AI summary
Provided is a method (100) and system (200) for recent user-activity image based authentication. The system collects (202) recent user-activity and location data, generates (214) user-knowledge events from the recent user-activity according to location data, generates (421) random image questions concerning the user-knowledge events based on location. The random image questions test the user's knowledge of their recent user-activity according to location. A generative Applications Programming interface (API) (140) parses (220) the answered image questions, queries (222) the database for an expected response to the answered image questions, and compares (224) the expected response to the answers received to authenticate the user. In some embodiments a DALL-E (161) component and a GPT-4 V (162) component are used together in conjunction for such purposes. Other embodiments are disclosed.