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Category Archives: Thoughts

Deep Learning is awesome and stupid

 

road-runner-tunnel-car

Can’t wait for hackers. We need to look beyond the hype cycle on Deep Learning. Deep Learning is ripe for new discoveries by security researchers.

Deep Learning very popular in recent years. Everyone is talking about Deep Learning and reference AI playing games and beating world champions in Go.

When you call out to Siri or Google for answers, Deep Learning is the technology solving those hard problems on the backend. Deep Learning has taken over image recognition and speech recognition. Self driving cars depend on Deep Learning.

Where do you start? What security controls would you put in place? How do you even secure Deep Learning?

Code and papers below on poisoning the system and creating examples to evade some basic vision systems.

These systems are weak. Securing Deep Learning systems are a green field.

Optical Illusions

http://www.michaelbach.de/ot/

Can’t wait for hackers. We need to look beyond the hype cycle on Deep Learning. Deep Learning is ripe for new discoveries by security researchers.

https://github.com/openai/cleverhans

http://karpathy.github.io/2015/03/30/breaking-convnets/

http://cs.stanford.edu/people/karpathy/break_linear_classifier.ipynb

https://people.eecs.berkeley.edu/~tygar/papers/SML/EECS-2008-43.pdf

https://da-data.blogspot.ca/2017/01/finding-bugs-in-tensorflow-with.html

https://people.eecs.berkeley.edu/~tygar/papers/SML2/Adversarial_AISEC.pdf

https://arxiv.org/pdf/1606.06565.pdf

https://arxiv.org/pdf/1412.6572v3.pdf

https://arxiv.org/pdf/1701.04079v1.pdf

https://arxiv.org/abs/1610.05820

http://vision.stanford.edu/cs598_spring07/papers/Lecun98.pdf

https://arxiv.org/abs/1312.6199

https://arxiv.org/pdf/1412.1897v4.pdf

https://arxiv.org/abs/1609.02943

https://arxiv.org/abs/1610.05820

https://arxiv.org/pdf/1611.01236.pdf

https://people.eecs.berkeley.edu/~tygar/papers/SML/EECS-2008-43.pdf

https://arxiv.org/abs/1611.03814

https://arxiv.org/abs/1611.03814

https://www.endgame.com/blog/endgame-research-aisec-deep-dga

https://conf.startup.ml/blog/adversarial

http://www.slideshare.net/pragroup/secure-kernel-machines-against-evasion-attacks

https://da-data.blogspot.ca/2017/01/finding-bugs-in-tensorflow-with.html

https://arxiv.org/pdf/1606.06565.pdf

https://arxiv.org/pdf/1312.6199v1.pdf

https://arxiv.org/pdf/1701.04079v1.pdf

http://vision.stanford.edu/cs598_spring07/papers/Lecun98.pdf

https://arxiv.org/abs/1312.6199

https://arxiv.org/pdf/1412.1897v4.pdf

http://cacm.acm.org/magazines/2016/11/209133-learning-securely/fulltext

https://arxiv.org/abs/1609.02943

https://arxiv.org/pdf/1412.6572.pdf

https://arxiv.org/abs/1611.03814

https://arxiv.org/abs/1611.03814

https://people.eecs.berkeley.edu/~tygar/papers/SML2/Adversarial_AISEC.pdf

http://composition.al/blog/2016/09/29/thoughts-on-adversarial-examples-in-the-physical-world/

https://conf.startup.ml/blog/adversarial

Main

https://people.eecs.berkeley.edu/~tygar/papers/SML2/Adversarial_AISEC.pdf

https://mascherari.press/introduction-to-adversarial-machine-learning/

https://arxiv.org/pdf/1606.04435v1.pdf

 

 

Agent based self driving car simulator

Backprop

DeepSounds

Style transfer – NIR –> RGB

Mathz 4 ML

The Titan XP challenge

Collection of detection solutions in Tensorflow

3 Pillars of Autonomous Driving

T-SNE attack data