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Model extraction attacks on Machine-Learning-as-a-Service platforms.
Dear Florian,
May I ask how may predictions the code needs to get one black box ANN(artificial neural network) or MLP in your paper? Suppose there are 200 neurons per layer, the total number of parameters is a lot.
Looking forward to your reply!
Thanks a lot!
In Steal-ML/trees/bigml_wrapper/experiments/models.py, it says:
# Download datasets using:
# curl "https://bigml.io/public/dataset/{DATA_ID}/download?$BIGML_AUTH" > ../data/bigml_datasets/{DATA_ID}.csv
It is not true; it will return with the 404 error, because bigml.io does not support "public/dataset" URI. The instruction might have worked five year ago, I assume.
You should redact BB_KEY
and username
in tree.py
.
Steal-ML/trees/bigml_wrapper/tree.py
Line 24 in e37c67b
When I execute lowd_meek.py using the same diabetes dataset specified in the code, the following error appears:
Expected 2D array, got 1D array instead:
array=[-0.529412 -0.035533 0.0491803 -1. -1. -0.0461997
-0.926255 -0.583333 ].
The above error comes from
label = self.clf1.predict(x)
in OnlineBase.py which is used when instantiating the class LordMeek in lowd_meek.py
What's the minimal example I can run a basic example of a black box attack?
I tried the crack-svm.py file but I encounter this error: AttributeError: 'LibSVMOnline' object has no attribute 'support_pts'
I tried to grep for this variable but it's non-existent in the files. Any idea how this variable can be retrieved?
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