Time distribution: is it possible to determine whether calls are human-made or machine-made by patterns of the distribution I'm relatively new to statistics, so the question is primarily about your advice on where I should start with this problem and read related material.
So, suppose I've got a temporal distribution of phone calls of a suspicious subscriber, a very basic one with just a timestamp of a successful phone call and a duration of it:
timestamp:duration
timestamp:duration 
...

The task is to test whether this subscriber is a bot (a machine) or a human.
Can you judge from such a distribution if a subscriber is indeed a human or a bot?
I've got distributions of other subscribers, a lot of them, and they are indeed human.
Is there a way I could compare phone call patterns of real humans with this suspicious distribution to tell if it resembles human behaviour?
Should I employ Poisson distribution for such a test instead?
What is the correct toolbox for such a task?
Thank you

Over the short term the answer is maybe. If we assume yes, then as soon as it becomes possible to model human-made calling patterns versus machine-made calling patterns, that very model can be used to generate machine-made calling patterns which are indistinguishable from human ones.
Over the long term, if being undifferentiable from human-made calling patterns provides some advantage to the owners or managers of machine callers, then the answer will become no as machine-call patterns camouflage themselves to be indistinguishable from human-made.
