How can I train a neural network to detect subliminal messages? Is there a way to train a neural network to detect subliminal messages? Where can I find the dataset on which to train the neural network?

If I have to create the dataset, how would I go about it?

United Nations has defined subliminal messages as perceiving messages without being aware of them, it is unconscious perception, or perception without awareness. Like you may be aware of a message but cannot consciously perceive that message in the form of text, etc. 

There are two many types of subliminal messages, one which can be made through visual means, another which can be made through audio. 

In visual means, I'm referring to these types:


Messages which are flashed for very short while on the screen. 
Messages whose opacity is changed to blend with the background.
Messages whose colors are varied slightly to blend with the background. 


Example of 3rd type of subliminal messages: if there is a background of red, on this can be shown a message made up of slight variation of red, as a conscious mind can't distinguish between such close shades of red, people will take the entire thing to be red block, but a subconscious mind notice the slight variation in color, register the message, because humans can see millions of colors.
Setting aside the dubious nature of subliminal messages. You have to clearly define what subliminal is. In all your cases presented, a manual algorithmic approach would be better. An ANN would tend to average out the subliminal messages as noise, just as your brain would. In the case of #2, #3, it's a matter of contrast, in which case computer vision methods of bringing out low contrast details to the forefront combined with a manual algorithm (perhaps an OCR pass for content not expected to have text) would be the way to go. ANN are not magic bullets, and still need to be used appropriately.