U. S. Bank Corporation

Samuel A Assefa

Ali Fathi

Ahmed Mohammed Abdelrahman Mohammed

Michael Jude Villano

Systems and methods to identify blockchain anomalies include an AI tool comprising a processor, a GPU, and a GNN model to extract graph parameters from a block transactions graph of a blockchain block, generate statistical approximations of the graph based on the graph parameters, compare the statistical approximations to at least one anomaly threshold, detect an irregular graph pattern in the graph when the statistical approximations exceed the at least one anomaly threshold, identify via the GNN model an anomaly within the block transactions graph based on the irregular graph pattern, generate via the GPU an address graph based on the block transactions graph when the anomaly is identified to display one or more addresses associated with the anomaly, and generate an alert when the anomaly is identified.

Systems and methods for real-time identification of an anomaly of a block transactions graph of a blockchain

A system and method includes receiving input and an identification, calculating a bias direction with respect to the identification for an embedding model used by an initial model, and calculating protected gradient scores for tokens in the input. The protected gradient scores are calculated by determining directional derivatives based on model output and bias direction to generate protected gradients, and calculating dot products of the protected gradients and bias direction. The token-level protected gradient scores are aggregated to form an input-level protected gradient score, which is used to determine a fairness indicator. If the fairness indicator is below a threshold, deployment of the initial model is prevented and the model is retrained or fine-tuned using training data selected based on the fairness indicator and identification to produce a trained model with reduced bias. The training data may be selected by removing biased data or synthetically generating new unbiased data.

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Dallas, TX, United States of America

Samuel A Assefa