Adversarial Noise Injection for Audio Signal Privacy
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Solution Overview
Problem
Existing computing systems lack effective adversarial protection for audio signals against automated analysis, which can lead to data privacy violations and interception of sensitive information.
Innovation Solution
The introduction of adversarial noise at the phoneme, word, or sentence level on audio devices to misclassify audio signals, preventing automated analysis and enhancing data privacy, while maintaining intelligibility for humans.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If adversarial noise is added to audio signals to prevent automated analysis, then data privacy and security are improved, but audio quality and intelligibility deteriorate
Solution Approach 1:
The patent applies parameter changes by modifying the audio signal in the frequency domain through spectral processing. Adversarial noise is injected at specific frequency bands while preserving the temporal structure and intelligibility of the speech signal, thus changing the spectral parameters without destroying the semantic content.
Solution Approach 2:
The patent implements local quality by applying different levels of adversarial noise to different segments of the audio signal. Instead of uniformly degrading the entire audio stream, the system selectively adds noise to specific time-frequency regions where automated analysis is most vulnerable, while preserving quality in regions critical for human intelligibility.
2Reliability
If adversarial noise is applied to misclassify audio signals, then automated analysis accuracy deteriorates, but communication intelligibility for humans is maintained
Solution Approach 1:
The patent uses an intermediary approach by introducing adversarial noise as a mediator between the original audio signal and the automated analysis system. This intermediary element confuses the automated analysis algorithms while remaining transparent to human listeners, effectively shielding the true meaning from automated extraction.
Solution Approach 2:
The patent applies partial action by adding only the minimum necessary amount of adversarial noise required to misclassify the audio signal. The noise level is carefully controlled to be just sufficient to defeat automated analysis algorithms while remaining below the threshold that would impair human intelligibility.
3Reliability
If security defenses are implemented against automated audio analysis, then data protection is improved, but system complexity increases
Solution Approach 1:
The patent implements self-service by enabling the audio device to automatically generate and apply adversarial noise without requiring external security infrastructure. The system uses the device's own processing capabilities to shield its audio outputs, eliminating the need for separate security systems or additional hardware.
Solution Approach 2:
The patent merges the security function with the existing audio processing pipeline by combining adversarial noise generation with the standard audio encoding and transmission processes. This integration allows security protection to be implemented as a natural extension of normal audio operations rather than a separate complex system.
Data Source
AI summary
Embodiments for providing adversarial protection of speech in audio signals by a processor. Security defenses on one or more audio devices may be provide against automated audio analysis of audio signals by using adversarial noise.