They can only fool the DNN because they know their weights. In theory, you could do the same for people's brains.
As long as you don't publish the specs of your net you should be fine I guess.
As long as you don't publish the specs of your net you should be fine I guess.
An oracle, here, would be any version of the system that you can query against repeatedly without suffering too much of a penalty.
The purpose of this research is to work as a proof of concept. Sure, this iteration needs to cheat slightly to achieve its results. However, looking at the images that aren't just noise, it seems to be possible to construct less specialized images that fool many nets.
No because the instant you used an image that was close, but wrong the human brain would retrain.
I wonder in the neural net can do the same - try this experiment on an active neural net and let it train itself. (i.e. don't tell it it's being faked, let it figure it out then correct for it).