A Multiparty Homomorphic Encryption Approach to Confidential Federated Kaplan Meier Survival Analysis

• URL: http://arxiv.org/abs/2412.20495v1
• Date: Sun, 29 Dec 2024 15:17:42 GMT
• Title: A Multiparty Homomorphic Encryption Approach to Confidential Federated Kaplan Meier Survival Analysis
• Authors: Narasimha Raghavan Veeraragavan, Svetlana Boudko, Jan Franz Nygård,
• Abstract summary: We propose a.<n>multiparty homomorphic encryption-based framework for.<n>privacy-preserving federated Kaplan--Meier survival analysis.<n>Our framework ensures encrypted survival estimates closely match centralized outcomes, supported by formal utility-loss bounds.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The proliferation of healthcare data has expanded opportunities for collaborative research, yet stringent privacy regulations hinder pooling sensitive patient records. We propose a \emph{multiparty homomorphic encryption-based} framework for \emph{privacy-preserving federated Kaplan--Meier survival analysis}, offering native floating-point support, a theoretical model, and explicit reconstruction-attack mitigation. Compared to prior work, our framework ensures encrypted federated survival estimates closely match centralized outcomes, supported by formal utility-loss bounds that demonstrate convergence as aggregation and decryption noise diminish. Extensive experiments on the NCCTG Lung Cancer and synthetic Breast Cancer datasets confirm low \emph{mean absolute error (MAE)} and \emph{root mean squared error (RMSE)}, indicating negligible deviations between encrypted and non-encrypted survival curves. Log-rank and numerical accuracy tests reveal \emph{no significant difference} between federated encrypted and non-encrypted analyses, preserving statistical validity. A reconstruction-attack evaluation shows smaller federations (2--3 providers) with overlapping data between the institutions are vulnerable, a challenge mitigated by multiparty encryption. Larger federations (5--50 sites) degrade reconstruction accuracy further, with encryption improving confidentiality. Despite an 8--19$\times$ computational overhead, threshold-based homomorphic encryption is \emph{feasible for moderate-scale deployments}, balancing security and runtime. By providing robust privacy guarantees alongside high-fidelity survival estimates, our framework advances the state-of-the art in secure multi-institutional survival analysis.

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