Hi all, I am a bit new in deep learning filed and actually I use CNN and MLP to do side channel attacks. To do this attack I train models with power or electromagnetic signals leaking from small devices. It means that the training data I use are too noisy. The observation that brought me here was that when I increased the training sample size (from 50000, to 450000 with 50000 step size) my model performance did not increase or even decreased(we define model performance with a different metric, not the accuracy or other common ML performance metrics). So in... (read more)
Hi all, I am a bit new in deep learning filed and actually I use CNN and MLP to do side channel attacks. To do this attack I train models with power or electromagnetic signals leaking from small devices. It means that the training data I use are too noisy. The observation that brought me here was that when I increased the training sample size (from 50000, to 450000 with 50000 step size) my model performance did not increase or even decreased(we define model performance with a different metric, not the accuracy or other common ML performance metrics). So in... (read more)