Countering the Rise of Adversarial ML
The security community has found an important application for machine learning (ML) in its ongoing fight against cybercriminals. Many of us are turning to ML-powered security solutions like NSX Network Detection and Response that analyze network traffic for anomalous and suspicious activity. In turn, these ML solutions defend us from threats better than other solutions can by drawing on their evolving knowledge of what a network attack looks like.
Attackers are well-aware of the fact that security solutions are using AI and ML for security purposes. They also know that there are certain limitations when it comes to applying artificial intelligence to computer security. This explains why cyber criminals are leveraging ML to their advantage in something known as adversarial machine learning.
In this post I’ll explain just what adversarial machine learning is and what it is not. To start, the label itself can be a bit misleading. It sounds like criminals are actually using ML as part of their attack. But that is not the case. The simple explanation is that they’re using more conventional methods to understand how security solutions are using ML so that they can then figure out how to Continue reading




