Fresh off raising an additional $11 million in financing, Edgewise Networks this week launched a platform that enables organizations to apply microsegmentation via a single mouse click.
Edgewise Networks CEO Peter Smith said the company’s Zero Trust Auto-Segmentation platform employs machine learning algorithms and analytics to discover the topology of the application environment and the communication pathways that might be exploited by cybercriminals.
Designed to be deployed either in a public cloud or on-premises IT environment, the Zero Trust Auto-Segmentation platform uses the data it collects to enable organizations to create a zero-trust application environment by enforcing policies that limit how applications are allowed to communicate with one another, Smith said. Organizations then can microsegment applications via a single click rather than needing to rely on complex network virtualization overlays that are more expensive to deploy and considerably less flexible, he noted.
Those policies not only can travel with the application as it moves between IT environments, but they also can be applied all the way down to the identity management level, he added, noting cybersecurity teams can also interrogate the AI models the Zero Trust Auto-Segmentation platform generates to ensure they have full transparency into how those policies are being applied.
Finally, Edgewise Networks is also developing a speech interface through which cybersecurity administrators will be able to apply microsegmentation using verbal commands.
Interest in microsegmentation has risen considerably as organizations realize how porous the network perimeter has become. Now, most assume malware is lurking somewhere within the IT environments. Should a piece of malware become activated, microsegmentation prevents it from replicating itself laterally throughout the IT environment, thereby limiting the amount of damage that can be inflicted to a smaller segment of the application portfolio. However, microsegmentation using virtual network overlays requires a lot of ongoing collaboration between cybersecurity, networking and application development teams. Edgewise Networks is making a case for an approach to microsegmentation that cybersecurity professionals can implement on their own.
On top of that capability, Smith said Edgewise Networks is extending its investments in machine learning algorithms to create a classification system that will alert cybersecurity teams to potential risks based on the threat data and user behavior analytics Edgewise has collected.
Smith noted that, given the level of automation that exists outside of cybersecurity, it seems comparatively anachronistic for organizations to still rely on arcane manual processes to implement cybersecurity policies. The approach being taken by Edgewise Networks essentially enables cybersecurity teams to regain control over their IT environments, he noted.
Increased collaboration between cybersecurity professionals, network administrators and application developers is a noble goal. However, there are plenty of times when cybersecurity professionals just need to be able to implement a policy control as quickly as possible without waiting for someone else to implement it on their behalf, especially when those who cybersecurity professionals are relying on already have a few hundred pressing matters of their own to address.