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Vulnerabilities of machine learning infrastructure

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Vulnerabilities of machine learning infrastructure

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The boom of artificial intelligence brought to the market a set of impressive solutions both on hardware and software sides. On the other hand, massive implementation of AI in various areas brings about problems, and security is one of the greatest concerns. The speaker will present results of hands-on vulnerability research of different components of AI infrastructure, including NVIDIA DGX GPU servers, ML frameworks, such as PyTorch, Keras, and TensorFlow, data processing pipelines and specific applications, including medical imaging and face recognition–powered CCTV. Updated Internet Census toolkit based on the Grinder framework will be introduced.

The boom of artificial intelligence brought to the market a set of impressive solutions both on hardware and software sides. On the other hand, massive implementation of AI in various areas brings about problems, and security is one of the greatest concerns. The speaker will present results of hands-on vulnerability research of different components of AI infrastructure, including NVIDIA DGX GPU servers, ML frameworks, such as PyTorch, Keras, and TensorFlow, data processing pipelines and specific applications, including medical imaging and face recognition–powered CCTV. Updated Internet Census toolkit based on the Grinder framework will be introduced.

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