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A Critical Overview of Privacy in Machine Learning

Emiliano De Cristofaro

2021IEEE Security & Privacy62 citationsDOIOpen Access PDF

Abstract

This article reviews privacy challenges in machine learning and provides a critical overview of the relevant research literature. The possible adversarial models are discussed, a wide range of attacks related to sensitive information leakage is covered, and several open problems are highlighted.

Topics & Concepts

Adversarial systemComputer scienceInformation leakageData scienceArtificial intelligenceComputer securityMachine learningPrivacy-Preserving Technologies in DataAdversarial Robustness in Machine LearningCryptography and Data Security
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