How AI Brings Greater Accuracy, Speed, and Scale to Microsegmentation

Microsegmentation is a security strategy that divides a network into small, isolated segments. This makes it more difficult for attackers to move laterally within the network if they are able to breach one segment. Microsegmentation is a key component of zero trust security, which is a security model that assumes that no user or device is trusted by default.

AI and machine learning (ML) can be used to improve the accuracy, speed, and scale of microsegmentation. AI can be used to automate the process of creating and enforcing security policies, as well as discovering and mapping workloads and dependencies. ML can be used to learn the behavior of the network and identify anomalies that could indicate a security breach.

Fields of Use

Here are some of the ways that AI and ML can be used to improve microsegmentation:

Automating policy creation and enforcement: AI can be used to automate the process of creating and enforcing security policies. This can help to reduce the time and effort required to implement microsegmentation, and it can also help to ensure that policies are consistently applied across the network.
Discovering and mapping workloads and dependencies: AI can be used to discover and map workloads and dependencies in the network. This information can be used to create more granular security policies that are tailored to the specific needs of each workload.
Adapting to dynamic changes in the environment: AI can be used to adapt to dynamic changes in the environment. For example, if a new workload is added to the network, AI can be used to automatically create a security policy for that workload.
Providing visibility and analytics: AI can be used to provide visibility and analytics into the network. This information can be used to identify anomalies that could indicate a security breach.

There are a number of AI and ML solutions for microsegmentation available from vendors such as Illumio, Zscaler, VMware, Cisco, and Guardicore. These solutions can help organizations to improve the accuracy, speed, and scale of their microsegmentation efforts.

Advantages

Here are some of the benefits of using AI and ML for microsegmentation:

Increased accuracy: AI can help to ensure that security policies are accurately applied to the network. This can help to reduce the risk of security breaches.
Increased speed: AI can automate the process of creating and enforcing security policies, which can help to speed up the implementation of microsegmentation.
Increased scale: AI can be used to scale microsegmentation to large, complex networks.
Reduced costs: AI can help to reduce the cost of implementing and managing microsegmentation.

AI and ML can be a valuable tool for improving the accuracy, speed, and scale of microsegmentation. By automating the process of creating and enforcing security policies, as well as discovering and mapping workloads and dependencies, AI can help organizations to more effectively protect their networks from cyberattacks.