#backup--Cobalt Iron Inc. today announced that it has received another new patent, this time for machine learning-driven cyber inspection. Issued on Sept. 19, U.S. Patent 11765187 introduces new capab...
LAWRENCE, Kan.: #backup--Cobalt Iron Inc. today announced that it has received another new patent, this time for machine learning-driven cyber inspection. Issued on Sept. 19, U.S. Patent 11765187 introduces new capabilities for Cobalt Iron Compass®, an enterprise SaaS backup platform. When fully implemented, the new techniques will apply machine learning analysis to determine which cyber inspection tools are most appropriate and effective for given data or cyber threats. They will also allow businesses to adjust proactively and automatically to which, how, and when cyber inspection tools are used to validate corporate data. This optimizes cyber inspection operations, thus improving cyber event detection and data validation processes.
Cyber attacks are increasing in frequency and sophistication. While businesses continue to harden various resources and parts of the IT environment, nefarious characters continue to change their attack approaches and targets. Cyber protections that worked yesterday or are working today may be insufficient in the near future. Companies also need more insights into how well their cyber resiliency schemes are working. In particular, analytics around cyber protection, detection, and inspection operations are woefully lacking in the industry.
This invention addresses those concerns. It qualified for a patent because of several unique characteristics:
This patent introduces machine learning technology advancements that will refine and optimize how Compass applies multiple cyber inspection tools depending on the conditions. Specifically:
For example, Compass might use these techniques to analyze cyber attack patterns and targets, recognize specific types of data or applications being targeted, and automatically restrict access control to similar types of data or applications in the enterprise.
In another instance, the technology might enable Compass to analyze machine learning training data from previous cyber attacks and previous cyber inspection operations to determine whether a different cyber inspection tool or a different level of inspection would be more effective at detecting particular types of cyber attack patterns. And if so, it may dynamically adjust the cyber inspection tool or level of inspection it performs against particular types of data in future cyber inspection operations.
The business outcome: lower risk of undetected cyber security events and continually improved data validation operations.
“Organizations are in dire need of more proactive assistance in protecting their data and other IT resources and in detecting suspicious cyber activities,” said Rob Marett, chief technology officer at Cobalt Iron. “These new techniques apply machine learning analysis to figure out in advance which cyber inspection tools will be best for different scenarios. This allows businesses to continually optimize cyber inspection operations, thus improving their ability to detect cyber events and validate data.”
Learn about Cobalt Iron:
Cobalt Iron Secures Patent on Applying Machine Learning to Cyber Inspection
Fonte: Business Wire
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