Secure Speech Recognition Frequency Filtering
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Solution Overview
Problem
Speech recognition systems are vulnerable to unauthorized control through inaudible voice commands that are not detected by humans, posing a security risk in controlling connected devices.
Innovation Solution
A secure speech recognition system filters received voice commands by frequency to identify commands outside the human audible range, creating in-band and out-of-band audio files, and calculates an attack risk based on these files to determine if the request is legitimate, alerting the user if the risk exceeds a threshold.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If speech recognition systems accept all voice commands without frequency filtering, then the system is easy to operate and responsive, but the system becomes vulnerable to unauthorized control through inaudible commands
Solution Approach 1:
The audio frequency spectrum is segmented into multiple bands (e.g., 20Hz-20kHz for human hearing, and other frequency ranges). The system processes each band separately, allowing it to identify and block commands in unauthorized frequency ranges while maintaining normal operation in the audible range. This segmentation enables security filtering without requiring complete system redesign.
Solution Approach 2:
An intermediary processing layer is introduced between audio input and command execution. This intermediary analyzes the frequency content of incoming audio signals and determines whether they represent legitimate user commands or potential attacks. The intermediary can filter or flag suspicious commands before they reach the execution layer, providing security without significantly altering the user interface.
2Reliability
If the system filters audio by frequency to detect malicious commands, then security is improved, but the processing time and computational resources increase
Solution Approach 1:
The system performs preliminary frequency analysis on incoming audio signals to identify potential threats before full speech recognition processing occurs. By detecting suspicious frequency patterns early in the pipeline, the system can quickly reject malicious commands without investing computational resources in complete transcription and interpretation, thereby reducing overall processing time for security-critical operations.
Solution Approach 2:
The patent replaces complex mechanical or computational analysis with simpler frequency-based detection mechanisms. Instead of analyzing the full semantic content of every audio signal, the system uses frequency filtering and spectral analysis to quickly identify anomalous patterns. This substitution of detailed analysis with pattern recognition at the frequency level reduces computational overhead and processing time.
3Reliability
If the system blocks commands outside the human audible range, then unauthorized control is prevented, but legitimate commands from assistive devices may be rejected
Solution Approach 1:
The system applies different quality controls to different frequency bands based on their likely sources and purposes. Audio in the human audible range (20Hz-20kHz) receives standard processing, while audio in other frequency ranges undergoes additional verification or is blocked. This localized quality control allows the system to maintain compatibility with human users while preventing unauthorized control through inaudible commands.
Solution Approach 2:
The system incorporates feedback mechanisms to learn from legitimate uses of non-audible frequencies. When authorized devices or users establish patterns of legitimate communication in specific frequency ranges, the system adapts its filtering rules to allow these patterns while maintaining security against unauthorized access. This feedback-driven adaptation balances security with compatibility.
Data Source
AI summary
Methods, systems and computer program products for operating a secure speech recognition are provided. Aspects include receiving a speech recognition request from a user, the speech recognition request including a captured audio file and filtering the captured audio file to create an in-band audio file and at least one out-of-band audio file. Aspects also include creating an in-band text file based on the in-band audio file and creating an out-of-band text file based on the out-of-band audio file. Aspects further include calculating an attack risk based at least in part on the in-band text file and the out-of-band text file. Based on a determination that the attack risk is below a threshold value, aspects include executing the speech recognition request.