DIFFERENTIALLY PRIVATE VARIATIONAL AUTOENCODERS FOR DATA OBFUSCATION

    公开(公告)号:US20240427936A1

    公开(公告)日:2024-12-26

    申请号:US18827444

    申请日:2024-09-06

    Applicant: SAP SE

    Abstract: Techniques for implementing a differentially private variational autoencoder for data obfuscation are disclosed. In some embodiments, a computer system performs operations comprising: encoding input data into a latent space representation of the input data, the encoding of the input data comprising: inferring latent space parameters of a latent space distribution based on the input data, the latent space parameters comprising a mean and a standard deviation, the inferring of the latent space parameters comprising bounding the mean within a finite space and using a global value for the standard deviation, the global value being independent of the input data; and sampling data from the latent space distribution; and decoding the sampled data of the latent space representation into output data.

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