A Study: Use of Machine Learning for Cyber Security

Machine learning is becoming prevalent in a variety of sectors, and machine learning algorithms are used in a variety of cyber security applications. Malware analysis, including zero -day malware detecting, risk evaluation, anomaly -based intrusion detection of common threats on critical systems, and other examples are just a few. Because signature -based methods are ineffective at detecting zero -day attacks or even slight modifications to existing attacks, researchers are employing machine learning (ML) -based identification in numerous security protocols. In this overview, we look at how machine learning is employed in several aspects of cyber -security. We also show how adversarial assaults on machine learning models can be used to change the data used to train and test models, rendering them useless.