Detecting Malicious Insiders
and Imposters by Monitoring User Journeys in Enterprise Applications
Reduce alert signal-to-noise ratio with unprecedented accuracy
Ubiquitous detection solution: SaaS, Cloud and custom-built applications
Eliminate rules, development and maintenance with user journey analytics
Reduce alert signal-to-noise ratio.
Ubiquitous detection solution.
Eliminate rules, development and maintenance.
Application Detection and Response (ADR)
Compliment current XDR and SIEM solutions with the missing layer of application detection. Other solutions focus mainly on the infrastructure, network, or access layers, but once the user has been authenticated, her/his activities within the business application are not monitored. This void is especially important for SaaS applications where access (i.e. CASB) is the only current detection solution.
Current detection solutions of malicious activities in the application layer are based on rules defined by log events generated by specific applications. However, rule-based solutions detect only known attack patterns, and they generate a high number of false alerts, requiring constant investment and maintenance. TrackerIQ’s user journey analytics is the next generation of application detection, eliminating the development and maintenance of detection rules.
TrackerIQ detection of user journeys is powered by innovative user journey analytics combined with a unique clustering engine, to automatically learn normal user journeys and accurately detect abnormal journeys which are indicative of malicious activities.
TrackerIQ detection is ubiquitous - applied on any application, and across applications, including SaaS applications, cloud applications and custom-built applications. It protects enterprise organizations against cases in which either an authenticated user is taking advantage of her/his permissions to perform malicious activities, or when an impersonator successfully bypasses authentication mechanisms to pose as a legitimate user.
Unmatched Accuracy with
User Journey Analysis
Detection technologies evolved from first generation rules to second generation statistical and volumetric analysis. However, both failed to deliver on the required accuracy. Next generation detection is context based, provided by the sequence of activities, which in applications are defined by the user journey. TrackeriQ’s ubiquitous user journey model is applied to any application log, which combined with a unique clustering engine, automatically learns normal user journeys and accurately detects abnormal journeys which are indicative of malicious activities.
PROUDLY TRUSTED BY
Focus on the Signals that Matter
4 Yaakov Rosen St, Ramat Gan 5246208, Israel