Gesture-Based User Verification With Dynamic Multi-Sensor Challenges
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Solution Overview
Problem
Existing verification systems face challenges in balancing security and user-friendliness, particularly in 3D environments, as malicious entities can exploit easy challenges and authorized users struggle with difficult ones, leading to compromised security and usability issues.
Innovation Solution
A verification system that uses a secured application on the user device to receive and execute challenges based on sensor data, locks sensors for challenge completion, and employs a trained model to determine user verification, ensuring only authorized access while maintaining usability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If verification challenges are made easy to improve user-friendliness, then authorized users can complete them successfully, but unauthorized users can also succeed in their malicious intents and compromise system security
Solution Approach 1:
The verification system dynamically adjusts challenge parameters based on risk assessment. The server evaluates device characteristics, sensor capabilities, and contextual factors to generate challenges with appropriate difficulty levels. This dynamic adaptation allows the system to maintain security while ensuring authorized users can complete challenges successfully.
Solution Approach 2:
The system changes verification parameters such as challenge type, number of required gestures, temporal constraints, and sensor combinations based on the assessed risk level and device capabilities. By modifying these parameters dynamically, the system balances security requirements with user-friendliness for different contexts.
2Reliability
If verification challenges are made difficult to improve system security, then unauthorized users are blocked, but authorized users struggle to complete the challenges and the system becomes unusable
Solution Approach 1:
The verification challenge difficulty is not fixed but dynamically adjusted based on multiple factors including device sensor capabilities, environmental context, and risk assessment. This ensures challenges remain difficult enough to block malicious entities while staying achievable for authorized users with legitimate devices.
Solution Approach 2:
The system uses the device's own sensors and characteristics to generate verification challenges tailored to that specific device. This self-service approach ensures challenges are appropriately calibrated for each device's capabilities, maintaining security without creating unnecessary barriers for authorized users.
3Ease of operation
If the same verification challenge is repeatedly used to improve user-friendliness, then authorized users become accustomed to it, but system security is reduced by affording malicious entities time and opportunities to break the challenge
Solution Approach 1:
The verification challenges are periodically updated and varied over time. The system implements temporal diversity by changing challenge parameters, types, and configurations at regular intervals or based on usage patterns. This periodic variation maintains user-friendliness through familiarity while preventing malicious entities from breaking static challenges.
Solution Approach 2:
The challenge configuration dynamically evolves based on system state, usage patterns, and security requirements. Rather than repeating static challenges, the system adapts challenge characteristics over time, ensuring both user comfort through gradual adaptation and security through continuous variation.
4Reliability
If multiple sensors are locked for verification to enhance security, then unauthorized access becomes more complex, but device complexity and processing requirements increase
Solution Approach 1:
The verification system segments the use of sensors by locking only the specific sensors required for the current challenge rather than all sensors. This selective locking approach enhances security through multi-sensor verification while minimizing device complexity by engaging only necessary components for each verification instance.
Data Source
AI summary
Systems and methods are provided for gesture-based verification of a user. A method includes receiving a request for verifying a user for an application, prompting the user to perform a series of gestures, capturing a data indicative of the user performing the series of gestures, and accessing a plurality of sets of weights, wherein each respective set of weights corresponds to a respective gesture of the series of gestures. The method includes configuring a gesture recognition model multiple times, each time of the multiple times corresponding to a respective set of the multiple sets of weights, where each set of weights corresponds to a gesture of the series of gestures. In response to recognizing all the gestures of the series of gestures, the method includes causing the application to provide access to at least one resource of the application based on the verifying the user.