Mutual Impact of Feature Selection and Privacy-preserving Mechanisms
Mina Alishahi,
Vahideh Moghtadaiee,
Amir Fathalizadeh
et al.
Abstract:Privacy concern has gained increased attention in data analysis, prompting the application of privacy-preserving methodologies. This includes private dataset generation techniques designed to conceal sensitive information, such as anonymization, Differential Privacy (DP), Generative Adversarial Networks (GANs), and Differentially Private GANs (DPGANs). Nonetheless, the utilization of these techniques can influence the importance of features within the privatized dataset, potentially impacting the accuracy and … Show more
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