Adaptive Noise Scaling
Implement mechanisms through custom Substrate pallets to adjust noise levels based on data sensitivity, applying higher noise to highly sensitive data (e.g., financial transactions) and lower noise to aggregated statistics.
Noise Adjustment in Financial Data
For example, in a dataset of financial transactions, higher noise would be applied to individual transaction amounts to prevent identification, while aggregated metrics like total transaction volume would receive less noise to maintain statistical accuracy, ensuring that AI models can still derive meaningful insights without compromising privacy while leveraging Substrate's governance mechanisms for parameter adjustment.
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