This is a research based on machine learning attacks.
This is a research based on machine learnig attacks and its vulnerability towards churn prediction models.
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Main Objective:-
To asses the effect of various adversarial attacks on a churn prediction model and attempt to increase model strength against the 3 types of attacks mainly Project gradient Descent attack, Boundary attack and Carlini attac.
Research Problem:-
How can we identify if churn prediction models we build are vulnerable to machine learning attacks or not and how can robust our model should be.
Individual research question and main objective:-
IT20268244 -
Main objective :
Study and analyze the project gradient descent attack and test how it affects the model implemented, Identify accuracy changes and propose methods to increase the said model strength against the attack.
Research Problem:-
Are Churn prediction models sensitive to project gradient descent attack?
How can we make our model robust against this attacks?
