nizarzerouale commited on
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559016e
1 Parent(s): b93991e

Update app.py

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  1. app.py +20 -13
app.py CHANGED
@@ -504,8 +504,9 @@ with demo:
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  gr.Markdown(
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  """
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- <h1 style="text-align: center;">Encrypted de-identification Audio Files Using Fully Homomorphic Encryption</h1>
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- <!-- <p align="center">
 
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  <a href="https://github.com/zama-ai/concrete-ml"> <img style="vertical-align: middle; display:inline-block; margin-right: 3px;" width=15 src="file/images/logos/github.png">Concrete-ML</a>
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  <a href="https://docs.zama.ai/concrete-ml"> <img style="vertical-align: middle; display:inline-block; margin-right: 3px;" width=15 src="file/images/logos/documentation.png">Documentation</a>
@@ -513,21 +514,27 @@ with demo:
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  <a href=" https://community.zama.ai/c/concrete-ml/8"> <img style="vertical-align: middle; display:inline-block; margin-right: 3px;" width=15 src="file/images/logos/community.png">Community</a>
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  <a href="https://twitter.com/zama_fhe"> <img style="vertical-align: middle; display:inline-block; margin-right: 3px;" width=15 src="file/images/logos/x.png">@zama_fhe</a>
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- </p> -->
 
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  """
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  )
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-
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  gr.Markdown(
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- """
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- <p align="center" style="font-size: 16px;">
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- Anonymization makes it impossible to identify a person from a data set and thus allows their privacy to be respected </p> Concealing some of PII information is a helpful technique for de-identification. However, this can't be considered as anonymization.
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- <p align="center" style="font-size: 16px;">
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- De-identification uses Fully Homomorphic Encryption (FHE) to conceal personally
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- identifiable information (PII) within encrypted documents, enabling computations to be
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- performed on the encrypted data.</p>
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- """
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- )
 
 
 
 
 
 
 
 
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  # Step 1: Add an audio file
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  gr.Markdown("## Step 1: Add an Audio File")
 
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  gr.Markdown(
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  """
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+ <h1 style="text-align: center;">Secure De-Identification of Audio Files</h1>
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+ <!--
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+ <p align="center">
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  <a href="https://github.com/zama-ai/concrete-ml"> <img style="vertical-align: middle; display:inline-block; margin-right: 3px;" width=15 src="file/images/logos/github.png">Concrete-ML</a>
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  <a href="https://docs.zama.ai/concrete-ml"> <img style="vertical-align: middle; display:inline-block; margin-right: 3px;" width=15 src="file/images/logos/documentation.png">Documentation</a>
 
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  <a href=" https://community.zama.ai/c/concrete-ml/8"> <img style="vertical-align: middle; display:inline-block; margin-right: 3px;" width=15 src="file/images/logos/community.png">Community</a>
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  <a href="https://twitter.com/zama_fhe"> <img style="vertical-align: middle; display:inline-block; margin-right: 3px;" width=15 src="file/images/logos/x.png">@zama_fhe</a>
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+ </p>
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+ -->
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  """
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  )
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+
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  gr.Markdown(
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+ """
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+ <p align="center" style="font-size: 18px;">
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+ Protecting personal data is more important than ever in today’s digital world. <b>Our project ensures privacy-preserving de-identification of audio data</b> using state-of-the-art <b>Fully Homomorphic Encryption (FHE)</b>, offering a secure and transparent solution for data anonymization.
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+ </p>
 
 
 
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+ <p align="center" style="font-size: 18px;">
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+ Traditional methods of de-identification often fall short of true anonymization, merely concealing identifiable information. With FHE, we go beyond obfuscation to provide <b>complete security,</b> allowing computations to be performed directly on encrypted data without ever exposing sensitive details.
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+ </p>
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+
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+ <p align="center" style="font-size: 18px;">
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+ This technology is crucial in enabling organizations to use and share sensitive data responsibly, while fully respecting individual privacy.
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+ </p>
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+ """
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+ )
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+
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  # Step 1: Add an audio file
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  gr.Markdown("## Step 1: Add an Audio File")