Using H2O Driverless AI for Cybersecurity

It is well-known that the Internet is the going to be the next battleground for everything to come. From misunderstandings, minor skirmishes, to fully-enabled state actors attacking governments. They are all positioned well to take advantage of: 1. The Cloak of the Internet 2. Remote attack locations 3. Asymmetry in impact 4. And an immense dependency of companies, people, governments, and every organization to be present on the internet. With this much at stake, the amount of resources that are poured into maintaining a secure network is remarkably low, and the job done by the people is nothing short of amazing. Unfortunately, this is limited in scale. And therefore, you need automated models. Automated-Machine-Learnt models do a tremendously quick and accurate job of detecting malicious behavior must faster, thereby averting any security violations. In this example, we will take datasets that should be vulnerable to potential attacks, and show how Driverless AI and the feature engineering capability can solve this problem.