Deficiency of correctly implemented and robust defence leaves Internet of Things devices
vulnerable to cyber threats, such as adversarial attacks. A perpetrator can utilize adversarial …

Adversarial attacks are implemented when an attacker introduces maliciously designed
inputs to deceive or corrupt machinelearning (ML) models. In this study, the researcher …

IoT sensors and sensor networks are widely employed in businesses. The common problem
is a remarkable number of IoT device transactions are unencrypted. Lack of correctly …

Adversarial attacks and defenses on cyber-physical systems is basically an AI (artifi cial
intelligence) technique that mimics the human mind, ie, the process of human thinking …

In today's world, machine learning is an emerging technology which is being used
extensively in different domains. In order to offer effective solutions in the broad area of …

The increasing adoption of machine learning models across various domains has brought to
light the critical issue of their vulnerability to adversarial attacks, raising concerns about their …

Aim and Scope The Covid-19 pandemic have accelerated a transition towards an era of
relying on cyberspace to intimately connect to the modern world with applications including …

Abstract Machine learning based system are increasingly being used for sensitive tasks
such as security surveillance, guiding autonomous vehicle, taking investment decisions …

Abstract Machine learning has the ability to learn in various conditions, and becomes a
research hotspot and an important direction for cyberspace defense. Unfortunately, machine …

There have been recent adversarial attacks that are difficult to find. These new adversarial
attacks methods may pose challenges to current deep learning cyber defense systems and …