Fingerprint Sensor Sub-Region Selection Against Latent Prints
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Solution Overview
Problem
Fingerprint sensors are susceptible to false positive authentication due to latent fingerprints, which are residue patterns left by authorized users, leading to security vulnerabilities.
Innovation Solution
Implementing a fingerprint sensor system that prompts users to place their finger within specific sub-regions of the sensor, selected to minimize the likelihood of latent fingerprints, and includes a control system to manage historical fingerprint and touch location logs to avoid areas with potential residues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the fingerprint sensor uses the entire sensing surface for fingerprint acquisition, then the ease of operation is improved, but the reliability deteriorates due to false positive authentication from latent fingerprints
Solution Approach 1:
The fingerprint sensing surface is divided into multiple sub-regions, and the system selects specific sub-regions for fingerprint acquisition based on historical data of latent fingerprint locations. This segmentation allows the sensor to avoid areas with latent fingerprints while maintaining user convenience.
Solution Approach 2:
The system performs preliminary actions by logging and analyzing historical fingerprint and touch locations to identify areas prone to latent fingerprints. This preliminary data collection enables the system to select safer sub-regions for authentication before actual fingerprint scanning occurs.
2Reliability
If the fingerprint sensor avoids sub-regions with latent fingerprints, then the reliability is improved, but the device complexity increases due to sub-region selection and historical data management
Solution Approach 1:
The control system performs self-service by automatically logging, analyzing, and using historical data to select optimal sub-regions for fingerprint acquisition. This self-service mechanism reduces the need for external intervention while managing system complexity through automated processes.
Solution Approach 2:
The system implements feedback loops where historical authentication results and touch location data are continuously analyzed to refine sub-region selections. This feedback mechanism allows the system to learn from past performance and improve reliability over time while managing complexity through iterative optimization.
Data Source
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AI summary
A method may include prompting a user to place their finger within a given sub-region of a fingerprint sensing surface and then obtaining the user's fingerprint. The given sub-region may be selected based on a determined or estimated probability that the given sub-region contains a latent fingerprint. As examples, the given sub-region may be determined randomly, pseudo-randomly, or based on information in a log of historical touch and/or fingerprint locations. The method may further involve tracking which sub-regions of the fingerprint sensing surface may potentially have latent fingerprints. The method may involve prompting the user to wipe one or more sub-regions of the fingerprint sensing surface when more than a predetermined fraction of the fingerprint-sensing surface has been used to obtain fingerprint images.