A prevalent misconception is that AIOps (Artificial Intelligence for IT Operations) in the IT department can only benefit IT. Instead, it benefits a number of other departments, right from network operators to security personnel.
According to Gartner, by 2023, 40% of enterprises will employ AIOps for application and infrastructure monitoring. AIOps products allow IT leaders to use AI and machine learning (ML) to detect threats and assess whether a prospective attack is a ransomware attack or a threat that could shut down data access. It can also reveal issues such as significant information leaks, which can result in permanent damage.
AIOps can be used in a variety of ways by security teams to detect threats. Listed below are a handful of the options.
Device visibility and speed
When it comes to security, the most critical factor is speed. Businesses should determine the originating location of a cyber-attack and when it occurred to get an advantage in catching cybercriminals and preventing cyber-attacks. AIOps platforms make use of network telemetry data acquired in real time. They can auto-discover, classify, and inventory devices using this information. They can also access all wireless, wired, and IoT devices that are connected to the cloud or the corporate network. Deep packet inspection (DPI) and other telemetry data collected over time can be used to map device communication. The security administrator receives a warning if device communication becomes abnormal and its behavior exceeds an AI-defined threshold.
Segmentation of the network
Network segmentation is one of the places where AIOps can help. Device classification can be used by AIOps to verify that corporate devices are connected to the correct virtual LAN or wireless set identifier. When it comes to edge security and including tools (AIOps) that can immediately help discover problems with connections, etc., network segmentation is critical.
How can security administrators employ AIOps?
While AI-enabled processes will go a long way, the usage of AIOps platforms for security objectives will require human intervention. Fine-tuning the device beyond the default automated discovery, for example, will assist in properly categorizing network components for behavior analysis. Furthermore, the AI within AIOps will need to be informed which apps, services, and other resources are regarded as business-critical. By identifying essential data flows, the AIOps platform will be able to better determine which security incidents are more important than others.
AIOps can provide precise information about the sort of threat, its effects, and what can be done to mitigate it when an alarm is issued. Administrators will be expected to respond to an alert, examine it, and take the recommended remediation measures. AIOps can be established to automate a response in specific instances. It’s more probable, however, that the administrator will be called in to help. Furthermore, if the advised remediation actions fail, the administrator will have to rely on alternative methods to do actual root cause investigation and prevent the threat on their own. As a result, while AIOps can help firms automate some IT security tasks, they are still a long way from not needing to hire or contract the required level of staff.