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    <h2>Rosetta</h2>
    <p>Rosetta is a privacy-preserving framework based on TensorFlow. It integrates with mainstream privacy-preserving computation technologies, including cryptography, federated learning and trusted execution environment. Rosetta aims to provide privacy-preserving solutions for artificial intelligence without requiring expertise in cryptography, federated learning and trusted execution environment. </p>
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          基于密码学等隐私计算技术为各行业数据流动中的隐私保护提供端到端解决方案
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      <h3>Feng Xiao</h3>
      <p>Ph.D. in Economics, Nankai University</p>
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      <h3>Lilin Sun</h3>
      <p>Master, Wuhan University</p>
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      <h3>Xinjun Liang</h3>
      <p>Fudan University, Bachelor in Genetic Engineering</p>
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      <h3><a href="https://github.com/xiexiangplaton">Xiang Xie</a></h3>
      <p>Ph.D., Trusted Computing and Information Assurance Laboratory, Institute of Software, CAS </p>
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  <h3> 在<a href="https://github.com/LatticeX-Foundation/Rosetta/graphs/contributors">GitHub</a>上</h3>
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      <h2>How Rosetta Works</h2>
      <p>Rosetta works by extending and hacking both Python frontend and the Operation Kernels in backend of TensorFlow. It decouples the development of TensorFlow-related components and privacy technology so that both developers from AI and cryptography can focus on what they are interested.</p>
    
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  <h2>Data Flow Graph and Operations</h2>
  <p>
    When running your Rosetta program, firstly the native TensorFlow data flow graph will be converted, and during this process the native Operations within the graph will be replaced with SecureOps.And at the second stage, the backend kernels of operations, implemented with specific cryptographic protocol, will be called to carry out underlying secure computation.
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    <h3>Build and Install Rosetta</h3>
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        <pre># clone rosetta git repository
git clone https://github.com/LatticeX-Foundation/Rosetta.git
cd Rosetta
# compile, install and run test cases
bash compile_and_test_all.sh</pre>
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<h2 class="toc"> Contents </h2>

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