Endpoint detection and response using machine learning

Abstract

The need for cybersecurity has increased manifold over the past decade due to an unprecedented shift towards digital. With the increase in the number and sophistication of threats, cybersecurity experts have been forced to seek out new and efficient ways to secure endpoints on a network. Machine learning provides one such solution. This paper discusses how IoT devices are threatened and the need for endpoint security. It overviews different Machine learning-based intrusion detection systems that are currently in use e.g., STAT, Haystack, etc., and other Endpoint Detection and Response Techniques.