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privacy-preserving

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This repository contains the code and data for the text re-identification attack presented in B. Manzanares-Salor, D. Sánchez, P. Lison, Evaluating the disclosure risk of anonymized documents via a machine learning-based re-identification attack, Data Mining and Knowledge Discovery, 2024.

  • Updated Oct 31, 2024
  • Python

FedAnil++ is a Privacy-Preserving and Communication-Efficient Federated Deep Learning Model to address non-IID data, privacy concerns, and communication overhead. This repo hosts a simulation for FedAnil++ written in Python.

  • Updated May 26, 2024
  • Python

FedAnil+ is a novel lightweight, and secure Federated Deep Learning Model to address non-IID data, privacy concerns, and communication overhead. This repo hosts a simulation for FedAnil+ written in Python.

  • Updated Sep 30, 2024
  • Python

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