Defending against Cyber Threats and Data Exfiltration with Advanced Security Analytics for Government Agencies
Protecting our Social and Armed Services’ Most Trusted Assets
Our mission is to provide identity-based threat detection and deterrence for on-premises and cloud-based architectures, to protect against insider threats, prevent data exfiltration and reduce excess access risks and abuse.
With Gurucul Risk Analytics (GRA), Federal cyber teams can realize the full potential of their investments while optimizing significant operational man-hours and mission precision. Gurucul delivers the intelligence and a force multiplier that uniquely enables Federal security teams to identify outlier anomalies, providing early warning alerts for complex threats that currently operate under the radar. Rules-based technologies only provide a historical understanding of attacks and miss the unknown unknowns. GRA’s predictive security analytics for government agencies technology, with machine learning, optimally manages the scale and complexity of the mission.
Top Features and Use Cases for Federal Agencies
- Predictive security analytics from user and entity behavior machine learning models
- Detection of account compromise, data exfiltration, access abuse and insider threats
- Identity analytics (IdA) to reduce the attack surface area due to excess access and access outliers
- Risk-based certifications for IAM (identity and access management), plus discovery of privileged access risks
- Self-audits for security awareness, deterrence and detection of identity and data theft
- Custom model development without coding or a minimal knowledge of data science
- Ability to model attributes from any desired dataset, including de-coupled big data