vicious-classifiers | Vicious Classifiers : Data Reconstruction Attack

 by   mmalekzadeh Python Version: Current License: MIT

kandi X-RAY | vicious-classifiers Summary

kandi X-RAY | vicious-classifiers Summary

vicious-classifiers is a Python library. vicious-classifiers has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

Privacy-preserving inference via edge or encrypted computing paradigms encourages users of machine learning services to confidentially run a model on their personal data for a target task and only share the model's outputs with the service provider; e.g., to activate further services. Nevertheless, despite all confidentiality efforts, we show that a ''vicious'' service provider can approximately reconstruct its users' personal data by observing only the model's outputs, while keeping the target utility of the model very close to that of a ''honest'' service provider. We show the possibility of jointly training a target model (to be run at users' side) and an attack model for data reconstruction (to be secretly used at server's side). We introduce the ''reconstruction risk'': a new measure for assessing the quality of reconstructed data that better captures the privacy risk of such attacks. Experimental results on 6 benchmark datasets show that for low-complexity data types, or for tasks with larger number of classes, a user's personal data can be approximately reconstructed from the outputs of a single target inference task. We propose a potential defense mechanism that helps to distinguish vicious vs. honest classifiers at inference time. We conclude this paper by discussing current challenges and open directions for future studies. We open-source our code and results, as a benchmark for future work.
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              vicious-classifiers has a low active ecosystem.
              It has 3 star(s) with 0 fork(s). There are 2 watchers for this library.
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              It had no major release in the last 6 months.
              There are 1 open issues and 0 have been closed. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of vicious-classifiers is current.

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              vicious-classifiers has no bugs reported.

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              vicious-classifiers has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

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              vicious-classifiers is licensed under the MIT License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

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              vicious-classifiers releases are not available. You will need to build from source code and install.
              Build file is available. You can build the component from source.
              Installation instructions are not available. Examples and code snippets are available.

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            Install vicious-classifiers

            You can download it from GitHub.
            You can use vicious-classifiers like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

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            gh repo clone mmalekzadeh/vicious-classifiers

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