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1. Initializing Dask Workers with cyBER... Initializing Dask Workers with cyBERT Model

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   from dask_cuda import LocalCUDACluster

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   from distributed import Client

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   import dask

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   def worker_init():

2. Create Streamz Workflow for cyBERT Create Streamz Workflow for cyBERT

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   def inference(messages):

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       worker = dask.distributed.get_worker()

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       df = cudf.DataFrame()

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       if type(messages) == str:

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           df["stream"] = [messages.decode("utf-8")]

3. Define Streamz Source for cyBERT Define Streamz Source for cyBERT

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   from streamz import Stream

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   consumer_conf = {

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           "bootstrap.servers": "localhost:9092",

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           "group.id": "group-1",

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           "session.timeout.ms": 60000,

4. rapidsai/clx rapidsai/clx Public archive

   A collection of RAPIDS examples for security analysts, data scientists, and engineers to quickly get started applying RAPIDS and GPU acceleration to real-world cybersecurity use cases.

   Jupyter Notebook 170 68

5. receptive_fields_via_spot_stim receptive_fields_via_spot_stim Public

   MATLAB

6. NESC533 NESC533 Public

   Neural Network Modeling Class

   MATLAB