Submitted by geoffroy_lesage t3_11zcc1a in deeplearning
geoffroy_lesage OP t1_jdbwzjj wrote
Reply to comment by the_Wallie in Question for use of ML in adaptive authentication by geoffroy_lesage
I'm not quite sure I understand: "Some unique fingerprint has to come from some sort of behavioral or bio data that can reasonably be assumed to uniquely identify a user"
--> you mean to say "you have to get something unique from the user directly"? Because there are many ways to acquire unique things about a user.... how they type words into a keyboard is a very unique one for example, and there are many metrics that can be measured to figure that out...
- Pressure, Duration of press, Duration between presses, Speed
- Accuracy of presses
- use of backspace, use of auto-correct
- use of emojis, punctuation
- length of phrases, length of text, etc
the_Wallie t1_jdd0t7w wrote
I don't think thst it's self-evident that all of those individual behaviors can actually yield a truly unique behavioral pattern per user for each type of app. Maybe when combined, if your app involves a lot of deep user interaction, but since you haven't shared what your app is supposed to actually do, it's impossible to give an informed opinion on your probability of success a priori, so all I can say is I'm skeptical but I wish you good luck building a solution.
geoffroy_lesage OP t1_jde7chs wrote
Fair enough, no there is no deep user interaction with the app it’s just a normal marketplace app, think Amazon app. I’ve just been relying on a bunch of research papers that seem to suggest that each of those data points individually yield unique profiles with high accuracy but I may be misunderstanding them… just a few:
- https://www.sciencedirect.com/science/article/pii/S1877050921015532
- https://www.sciencedirect.com/science/article/pii/S1877050918314996
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