AI and machine learning can play a key role in enhancing the capabilities of security staff. An integrated security platform that utilizes AI and machine learning reduce the burden on security teams by automating the process of combing through telemetry data to find critical insights that will boost a security posture. Massive amounts of data like the 9 trillion rows of telemetry monitored daily by a Global Intelligence Center, can be analyzed with AI to create context and relationships. This task would be impossible for a human analyst.
In addition, machine learning and AI can also be used to facilitate a risk assessment of an organization’s security posture. By deploying the technologies to parse through vast amounts of disparate data, organizations can identify their most prominent areas of risk and prioritize resources accordingly.
Machine learning models learn from the telemetry and combine different events that are seemingly unrelated, but if combined together with enough context, can identify a critical incident that would likely go unnoticed by an individual. Using machine learning and AI, we are now able to identify dramatically more critical events as part of its own security services than it could prior to the use of the technologies.
There are a lot of moving parts in the cloud and you don’t necessarily have a full picture of what’s going on. To effectively harness AI and ML on you need massive amounts of unbiased data. The recommended way to get this is by working with a partner that has global telemetry monitoring and analytics of cloud security incidents, and a proven track record with AI and ML. By doing so, you’ll have full confidence that the proverbial needle in the haystack won’t be missed, less obvious connections will be made, bad actors will be stopped, and that your company is properly safeguarded against potential risks.