Voice Biometric Updating With Synthetic Speech Anomaly Detection
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Solution Overview
Problem
Existing voice biometric systems fail to adapt to changes in a person's voice over time due to factors like aging, illness, and environmental conditions, leading to increased false rejection rates and susceptibility to synthetic voice attacks, compromising security and user satisfaction.
Innovation Solution
A method and system that analyze voice biometric data in real-time, update the data to reflect current voice characteristics, and securely store it using blockchain technology, with adaptive thresholds and anomaly detection to enhance security against synthetic speech.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If voice biometric data is stored statically in data records, then the system is simple and easy to operate, but the system cannot adapt to changes in a person's voice over time, leading to increased false rejection rates
Solution Approach 1:
The patent implements dynamic voice biometric data by continuously updating the data records with new voice samples captured during authentication transactions. The system transitions from static storage to dynamic evolution of voice templates, allowing the system to adapt to voice changes over time through automated updates without requiring manual re-enrollment.
Solution Approach 2:
The system incorporates feedback mechanisms where each authentication transaction provides feedback that triggers updates to the voice biometric data. The anomaly detection algorithm provides feedback about synthetic voice attempts, and the system uses this feedback to refine its understanding of legitimate voice patterns while blocking fraudulent attempts.
2Reliability
If static voice biometric data is used, then the system has low complexity, but it becomes increasingly susceptible to synthetic voice and deep fake attacks
Solution Approach 1:
The system performs preliminary actions by capturing voice biometric data during the authentication transaction itself, before the data can be used for potential synthetic voice attacks. The anomaly detection algorithm performs preliminary analysis to identify synthetic voice characteristics before authentication is completed, preventing fraudulent transactions from succeeding.
Solution Approach 2:
The patent introduces an anomaly detection algorithm as an intermediary between the voice authentication system and potential synthetic voice attacks. This intermediary layer analyzes voice characteristics in real-time, identifies anomalies associated with synthetic speech, and prevents fraudulent authentication attempts before they can compromise the system.
3Adaptability or versatility
If the system updates voice biometric data continuously, then adaptability to voice changes is improved, but the computational resources and processing time increase
Solution Approach 1:
The system applies partial action by updating voice biometric data selectively rather than continuously. The anomaly detection algorithm determines when updates are necessary based on detected anomalies or periodic triggers, rather than performing constant updates. This approach maintains adaptability while reducing unnecessary computational overhead.
Data Source
AI summary
A method for enhancing the security of voice biometric data is provided that includes receiving, by an electronic device, voice biometric data of a user captured while the user was speaking and analyzing the context in which the received voice biometric data was captured. The context includes environmental and situational factors. The method also includes analyzing characteristics of the received voice biometric data to detect anomalies associated with synthetic speech, and conducting a biometric authentication transaction based on the voice biometric data in response to determining the received voice biometric data is free of anomalies. In response to successfully authenticating the user, the method includes updating record voice biometric data of the user with the received voice biometric data. Moreover, the method includes modifying the updated record voice biometric data and securely storing the modified updated record voice biometric data.