Identifies risks, without having to establish rules or thresholds.
SAN FRANCISCO, Calif. (PRWEB) June 20, 2017
Fortscale Security Ltd., the pioneer in embeddable behavioral analytics, announced a new patent that moves the user and entity behavior analytics (UEBA) industry forward. The patent, “Identifying Insider-Threat Security Incidents via Recursive Anomaly Detection of User Behavior”, covers Fortscale’s advancements in machine-learning technology that enable the company’s embeddable engine to identify, alert and score anomalous activity to uncover insider threats.
The ground-breaking technology doesn’t use rules or thresholds to define behavior, rather it introduces Behavioral Analytics algorithms created specifically to establish the correct context behind the behaviors of users and entities in an organization’s environment. As a result, the technology is able to provide accurate, risk-based information (alerts) that helps expose the intent and threat-level of specific activity and identify cyberattacks.
“This patent is just another example of the advancements you can make when you have some of the brightest, most experienced security experts and software engineers working to solve some of the industry’s toughest problems,” said Ophir Rachman, CTO of Fortscale. “We are passionate about providing visibility into who is doing what within your mission-critical applications (billing systems, customer databases, code repositories, or other proprietary applications). This patented technology helps us accomplish that efficiently and effectively.”
The technology covered by the patent is available in Fortscale Presidio, the industry’s first embeddable UEBA engine that allows SIEM, EDR/EPP, DLP, CASB, IAM, Firewall and other security infrastructure vendors to integrate advanced behavioral analytics into their solutions. By embedding Presidio, security vendors can…