Playback Content Protection Using Dynamic Adversarial Noise
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Solution Overview
Problem
Existing data protection algorithms using adversarial noise and/or patches are static and may be easily bypassed by future machine learning algorithms, failing to provide long-term protection for content.
Innovation Solution
Implement a dynamic data protection scheme that regenerates adversarial noise and/or patches whenever content is played back, using a data protection algorithm that adapts based on current time, random numbers, or number of plays, and is optimized to protect against specific content manipulation algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If static adversarial noise and patches are applied to content, then protection against current content manipulation algorithms is improved, but protection against future algorithms deteriorates
Solution Approach 1:
The patent applies dynamics by transforming the static adversarial noise into dynamic noise that changes with each playback. The system uses a data protection algorithm that generates different adversarial noise patterns based on playback count, timestamp, and random values, ensuring the protection adapts to future algorithms while maintaining effectiveness against current ones.
Solution Approach 2:
The patent implements parameter changes by modifying key parameters of the adversarial noise including amplitude, frequency, phase, and temporal characteristics based on playback history and system state. This allows the same base noise pattern to evolve into multiple distinct variations that maintain protection effectiveness while adapting to different algorithmic threats.
2Adaptability or versatility
If dynamic data protection algorithm is applied to regenerate adversarial noise on each playback, then protection against future algorithms is improved, but computational complexity increases
Solution Approach 1:
The patent applies preliminary action by pre-computing and storing base adversarial noise patterns and their variations in advance. During playback, the system retrieves these pre-computed patterns and applies minimal transformations based on current playback parameters, significantly reducing real-time computational complexity while maintaining dynamic adaptation capabilities.
Solution Approach 2:
The patent implements partial action by applying data protection only during playback operations rather than continuously processing all content. The system selectively generates adversarial noise only when content is being reproduced, avoiding unnecessary computational overhead during storage and transmission phases.
3Reliability
If encrypted content data is decrypted for processing, then data protection is maintained, but security vulnerability increases during playback
Solution Approach 1:
The patent applies preliminary anti-action by embedding adversarial noise into the content data before decryption occurs during playback. The system prepares protected content in advance where the adversarial noise is integrated at the encoded level, creating a preemptive defense that activates automatically during decryption without requiring additional security measures during the vulnerable playback phase.
Data Source
AI summary
An information processing device, wherein the information processing device includes circuitry configured to:copy, in response to an instruction for play back of a content, encrypted content data;decrypt the copied encrypted content data for obtaining the content data representing the content; andapply a data protection algorithm on the content data to generate protected content data representing protected content, wherein the protected content is played back.


