How Machine Learning-Based Security Sees Risk Faster than Legacy Tools

Machine learning (ML) and artificial intelligence (AI) are in the process of changing almost every aspect of our lives. My last post focused on how AI can be used to help businesses manage their IT environments better. This post will look at the impact ML has on security. The biggest challenge with cybersecurity is that it’s hard and getting more difficult. Despite spending billions of dollars on security tools to help fight the bad guys, businesses are actually falling behind. A recent study from the Ponemon research group found that the mean time to identify a breach was 197 days and another 69 days to contain the breach. My research shows that this number has actually increased over the past five years as environments have become more complex. Looking ahead, trends like the cloud, containers and the internet of things will only add to the chaos that is corporate IT and those numbers (197 and 69) will continue to rise if things don’t change. One of the problems in cybersecurity is that the focus of the tools is incomplete. We have many tools that only protect company borders. While this is a key requirement, it’s insufficient.