What process can be used to prevent disruption with unknown OT devices during active probing?

Implementing passive learning before active scanning is a strategic approach that helps in preventing disruption caused by unknown operational technology (OT) devices. This process allows for the collection of data about devices on the network without the intrusive nature of active probing.

Passive learning involves monitoring network traffic to gather information about devices that are already present. It helps in identifying the types of devices, their behavior, and communication patterns without sending out probing signals that could potentially upset or disrupt sensitive OT devices. By understanding the network environment through passive means first, administrators can create a knowledge base of known devices and their characteristics, which enables more targeted and less intrusive active scanning later on.

This method significantly reduces the risk of inadvertently causing disruptions in critical operations that might be affected by aggressive active probing efforts. Without a solid understanding of the network's existing devices, probing could lead to unintended consequences, such as service interruptions or device malfunctions, particularly in environments where uptime is crucial.

In contrast, creating policies that block all probing or only allowing known devices to connect may overly restrict legitimate device discovery and make it difficult to manage the network effectively. Conducting constant active scanning could lead to significant network interruptions and is not typically a best practice for managing sensitive OT environments.