Fortinet has developed an architecture that enables unified data collection and analytics from diverse information sources including logs, performance metrics, SNMP Traps, security alerts, and configuration changes. FortiSIEM essentially takes the analytics traditionally monitored in separate silos - SOC and NOC - and brings that data together for a comprehensive view of the security and availability of the business. Every piece of information is converted into an event which is first parsed and then fed into an event-based analytics engine for monitoring real-time searches, rules, dashboards, and ad-hoc queries.
FortiSIEM uses Machine Learning to detect unusual user and entity behavior (UEBA) without requiring the Administrator to write complex rules. FortiSIEM helps identify insider and incoming threats that would pass traditional defenses. High fidelity alerts help prioritize which threats need immediate attention.
FortiSIEM build a risk scores of Users and Devices that can augment UEBA rules and other analysis. Risk scores are calculated by combining several datapoints regarding the user and device. The User and Device risk scores are displayed in a unified entity risk dashboard.