For the past several months, I've been engineering a solution to one of the biggest threats facing musicians and audio professionals: the unauthorized use of their work to train AI models. The result is STEM SAFE SOLUTIONS, and I'm looking for feedback from the HN community.
The system, called the EMPIRE ENGINE, is a multi-layered defense pipeline that processes and protects audio files before they are released. It's designed not just to watermark, but to actively degrade the value of any audio scraped for unauthorized AI training.
You can test the live system right now at the URL.
How it works:
When you upload an audio file, it passes through a 5-tier security process:
1. AI Data Poisoning: Injects subtle, inaudible adversarial noise designed to confuse and corrupt machine learning models if they try to learn from the track.
2. "Living Stem" Watermarking: A proprietary, dynamic digital watermark (FSK-based) that is resilient to common attacks like compression or format changes. It proves ownership and integrity.
3. AES-256 GCM Encryption: The core audio data is encrypted, and a secure fingerprint is generated.
4. Spectral Steganography: The ownership and file integrity data is embedded directly into the audio's spectrogram, making it part of the file itself.
5. Active Countermeasures: The system includes components that can detect, log, and neutralize threats in a production environment.
My goal is to give power back to creators. Our slogan is "WHERE MUSIC INJECTION MEETS CODE DETECTION".
I would appreciate any feedback on the concept, the execution, and any vulnerabilities you might find. Thank you.
For the past several months, I've been engineering a solution to one of the biggest threats facing musicians and audio professionals: the unauthorized use of their work to train AI models. The result is STEM SAFE SOLUTIONS, and I'm looking for feedback from the HN community.
The system, called the EMPIRE ENGINE, is a multi-layered defense pipeline that processes and protects audio files before they are released. It's designed not just to watermark, but to actively degrade the value of any audio scraped for unauthorized AI training.
You can test the live system right now at the URL.
How it works: When you upload an audio file, it passes through a 5-tier security process:
1. AI Data Poisoning: Injects subtle, inaudible adversarial noise designed to confuse and corrupt machine learning models if they try to learn from the track. 2. "Living Stem" Watermarking: A proprietary, dynamic digital watermark (FSK-based) that is resilient to common attacks like compression or format changes. It proves ownership and integrity. 3. AES-256 GCM Encryption: The core audio data is encrypted, and a secure fingerprint is generated. 4. Spectral Steganography: The ownership and file integrity data is embedded directly into the audio's spectrogram, making it part of the file itself. 5. Active Countermeasures: The system includes components that can detect, log, and neutralize threats in a production environment. My goal is to give power back to creators. Our slogan is "WHERE MUSIC INJECTION MEETS CODE DETECTION".
I would appreciate any feedback on the concept, the execution, and any vulnerabilities you might find. Thank you.