CyberArk Software has been granted a patent for a system that utilizes machine learning to assess network access risks. The technology builds customized behavioral profiles for identities, evaluates new events against these profiles, and determines risk levels to automate security responses without human intervention. GlobalData’s report on CyberArk Software gives a 360-degree view of the company including its patenting strategy. Buy the report here.

According to GlobalData’s company profile on CyberArk Software, Automation system authentication was a key innovation area identified from patents. CyberArk Software's grant share as of June 2024 was 60%. Grant share is based on the ratio of number of grants to total number of patents.

Automated network security risk assessment using machine learning

Source: United States Patent and Trademark Office (USPTO). Credit: CyberArk Software Ltd

The granted patent US12047392B2 outlines a non-transitory computer-readable medium and a computer-implemented method designed to automatically evaluate and respond to network security risks. Central to this innovation is the development of a customized behavioral profile for an identity, which is constructed using a machine-learning process that incorporates various inputs such as login location, time, device identification, IP address, and application used. The system identifies event clusters linked to both long-term and short-term memory based on this profile, allowing it to assess new events and determine their associated risk levels. The risk assessment is further refined by a confidence level that reflects the training maturity of the machine learning model. Based on these evaluations, the system can execute security actions, including generating authentication prompts, issuing alerts, or denying access to restricted resources.

Additionally, the patent details various enhancements to the core method, such as the ability to adjust confidence levels to minimize unnecessary authentication requests and the inclusion of additional inputs like command-line interface events and authorization escalations. The method also allows for the continuous updating of the behavioral profile based on the identity's activity, ensuring that the system remains responsive to changes in behavior. The security rules applied can be either default or customized, and the method includes mechanisms to filter out irrelevant data and convert input formats as needed. Overall, this patent presents a comprehensive approach to enhancing network security through intelligent risk assessment and adaptive response mechanisms.

To know more about GlobalData’s detailed insights on CyberArk Software, buy the report here.

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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.