Stop Threats in Real Time with Machine Learning Black Hat USA 2020

Automated and polymorphic attacks are being launched faster than traditional sandboxing and signature-based technologies can deploy protection. With thousands of variations of new malware being created in minutes, you’re exposed to more and more risk with each passing second.

In this session our Unit 42 threat research team will discuss how real world threats take root and spread rapidly. We’ll highlight how machine learning can be practically applied to not only analyze and detect threats, but block them at line speed to prevent initial infections and the resulting spread, stopping weaponized files, phishing and malicious scripts instantly without sacrificing business productivity or the need to deploy more security solutions.