Mitigating Explanation Leakage in Financial Fraud Detection Systems
This dissertation proposes and evaluates DP-FedSHAP, a new architecture that applies client-level differential privacy only to post-hoc TreeSHAP vectors and measures the trade-off between explanation fidelity, privacy preservation, and the model's Area Under the Precision-Recall Curve (AUPRC).