Detecting Malicious Insiders and Imposters by Monitoring User Journeys in Enterprise Applications
- Detect abuse, misuse and malice in applications
- Ubiquitous for and across SaaS and custom-built applications
- Unprecedented signal-to-noise ratio based on User Journey Analytics
Detecting Malicious Insiders and Imposters by Monitoring User Journeys in Enterprise Applications
- Detect abuse, misuse and malice in applications
- Ubiquitous for and across SaaS and custom-built applications
- Unprecedented signal-to-noise ratio based on User Journey Analytics
Unmatched Accuracy Based on User Journey Analytics
Application User Journey Analytics
User Journey Analytics is based on the analysis of activity sequences performed while using an application, in contrast with UEBA, which analyzes each activity on its own and then builds a timeline. The sequence provides enriched context for anomaly detection and enables unmatched accuracy based on journeys, as opposed to outcomes.
Multiple Journey Profiles per User
Leveraging the RevealSecurity clustering engine - tailored for clustering user journeys - TrackerIQ automatically learns multiple journey profiles per user and application. Detecting anomalous journeys via comparison to all common user’s journeys provides an extremely high signal-to-noise ratio.
Application Agnostic Detection
A ubiquitous detection model that is applied to any SaaS and custom-built application, analyzing user journeys in and between different applications to detect anomalies. Since no rules are required, it eliminates the need to fully understand the application business logic.
Application Layer XDR
Mainstream detection solutions are focused on the infrastructure layers and on access to business applications, resulting in very limited effectiveness against malicious insiders as well as external attackers who succeed to bypass authentication mechanisms. TrackerIQ complements existing XDR solutions with application detection based on user journey analytics to provide accurate monitoring and detection of application layer attacks.
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