On the (In-)Security of Machine Learning Nicholas Carlini Google - PowerPoint PPT Presentation

Oct 26, 2022 •330 likes •1.14k views

On the (In-)Security of Machine Learning Nicholas Carlini Google Brain Written: Sept 24, 2014 Written: Sept 24, 2014 Today: Oct 16, 2018 Written: Sept 24, 2014 Today: Oct 16, 2018 ... 4 years ago So how are we doing? 95% it is a

On the (In-)Security of Machine Learning Nicholas Carlini Google Brain
Written: Sept 24, 2014
Written: Sept 24, 2014 Today: Oct 16, 2018
Written: Sept 24, 2014 Today: Oct 16, 2018 ... 4 years ago
So how are we doing?
95% it is a French Bulldog
83% it is a Old English Sheepdog
78% it is a Greater Swiss Mountain Dog
67% it is a Great Dane
99.99% it is Guacamole
96% it is a Golden   Retriever
99.99% it is Guacamole
This phenomenon is known as an adversarial example B. Biggio, I. Corona, D. Maiorca, B. Nelson, N. Srndic, P. Laskov, G. Giacinto, and F. Roli. Evasion attacks against machine learning at test time. 2013. C. Szegedy, W. Zaremba, I. Sutskever, J. Bruna, D. Erhan, I. Goodfellow, and R. Fergus. Intriguing properties of neural networks. ICLR 2014. I. Goodfellow, J. Shlens, and C. Szegedy. Explaining and harnessing adversarial examples. 2014.
Why should we care about adversarial examples? Make ML robust
Why should we care about adversarial examples? Make ML Make ML robust better
How do we generate adversarial examples?
DEFN: The loss of a neural network on an input x for a label y is a measure of how wrong the network is on x .
loss( , dog) is small loss( , guacamole) is large
neural network loss   MAXIMIZE on the given input the perturbation is less SUCH THAT than a given threshold
What do we need to know? Everything.
WHY does this work?
Truck Dog
Truck Dog Airplane
( (
Okay, lesson learned.
Okay, lesson learned. Don't classify dogs with neural networks.
99.99% it is a School Bus
Okay, lesson learned.
Okay, lesson learned. images Don't classify dogs with neural networks.
And now for something And now for something And now for something completely different completely different completely different
Mozilla's DeepSpeech
Mozilla's DeepSpeech transcribes this as "most of them were staring   quietly at the big table"
Mozilla's DeepSpeech transcribes this as "most of them were staring   quietly at the big table"
What about this?
"It was the best of times, it was the worst of times, it was the age of wisdom, it was the age of foolishness, it was the epoch of belief, it was the epoch of incredulity"
Okay, lesson learned.
Okay, lesson learned. or audio Don't classify images with ^ neural networks.
Okay, lesson learned.
Okay, lesson learned. Don't let adversaries perform gradient descent.
Okay, lesson learned.
Okay, lesson learned. Don't let adversaries have ANY access to my model
Okay, lesson learned.
Okay, lesson learned. Give up.
Yes, machine learning gives amazing results
However, there are   also significant   vulnerabilities Guacamole (99%)
Questions? https://nicholas.carlini.com nicholas@carlini.com

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