Adversarial examples have emerged as a significant threat to machine learning algorithms,
especially to the convolutional neural networks (CNNs). In this paper, we propose two …

At the present time, machine learning methods have been becoming popular and the usage
areas of these methods have also increased with this popularity. The machine learning …

Most of the data manipulation attacks on deep neural networks (DNNs) during the training
stage introduce a perceptible noise that can be catered by preprocessing during inference …

The advancement in deep learning has taken the technology world by storm in the last
decade. Although, there is enormous progress made in terms of algorithm performance, the …

We propose a novel discrete-time dynamical system-based framework for achieving
adversarial robustness in machine learning models. Our algorithm is originated from robust …