“Make the trust zones smaller” is the rallying cry behind microsegmentation projects. Break up the network into smaller pieces and put firewalls in between those pieces to ensure attackers can’t get from one part of the network to the next. But making microsegmentation projects work relies on a great deal of knowledge of the network and attack pathways. And it’s an incredibly heavy lift–configuring and deploying a microsegmentation solution takes an immense amount of time and resources. Machine learning can significantly reduce the hurdles by learning the network’s intended state and defining the attack pathways that need to be secured, automating the microsegmentation process.
Edgewise’s Chief Data Scientist John O’Neil will deep-dive into the role of machine learning in microsegmentation and demonstrate how a machine learning driven solution could reduce the time and energy needed to deploy microsegmentation from months to hours.