Fortscale

Fortscale is the only pure-play machine learning UEBA product on the market. No rules to write. No limits on what Fortscale can detect. From its intuitive alerts and investigations, to its self-tuning anomaly detection and risk scoring, Fortscale is stacked with features designed to make the lives of security analysts easier.

Fortscale consumes, stores, and analyzes millions of individual events on a daily basis. All of that data needs to be within reach at a moment’s notice, which is why Fortscale is backed by Hadoop architecture. Big data architecture coupled with the machine learning-based Insider Threat Detection Engine allows Fortscale to scale to the largest environments in the world.

Fortscale SMART Alerts are triggered when the system identifies a threat, based on a collection of anomalies or indicators that together cross a statistical threshold that is unique for every user in your system. SMART Alerts are designed to provide analysts with specific semantic context about the threat that has been discovered, giving analysts a major head-start on understanding the state of their network during stressful incidents. FORTSCALE is software designed to identify hidden threats.

These threats could arrive from any source. This software makes the life of security analyst easy and undemanding. The software deliver all sort of data needed by security analysts and decision makers. The software has feature that makes job of security analyst, straight forward and undemanding. The software allow data ingestion and enrichment. Under this feature behavioral data is ingested and enriched with contextual data.

The software has the feature for anomaly detection. Changes in behavior which may hint a malicious activity can be detected by creating a baseline. Multi-dimensional baselines are created to identify changes in behaviors. The software scores the risk and data analysis is performed. Risk scoring allows in determining the severity of threats and risks to the organization.

The software provides a quick review of threats and risks that might attack a company. Threats can be identified by the analyst only by clicking few features of the software. Thus, threat detection is an easy and quick job. The software analyzes behavioral and contextual data to detect threats. The software develops a baseline through data collection in order to identify threats. Changes in behavior is analyzed through statistical analysis and machine learning to detect insider threats. The software prioritizes risks and threats through various analysis. These analysis include iterative analysis and multivariate correlations. The software collects huge volumes of data to detect malicious event. The software produce reports for security analysts. The software provides powerful techniques to detect risk that may hamper company performance.