Millions of alerts are generated by best-of-breed technologies deployed within your organization and writing correlation rules and policies to find actionable events can only address one part of the problem statement – YOU CAN WRITE RULES TO LOOK FOR ISSUES YOU KNOW BUT WHAT ABOUT THE UNKNOWN?
HOW GURUCUL CAN HELP
Gurucul’s Threat Analytics Platform is built upon our core architecture PIBAE (Predictive Identity Based Behavior Anomaly Engine) to identify anomalous behaviors of malicious insiders and comprised accounts by leveraging contextual identity based behavior analytics, machine learning, and peer group modeling.
Our big data enabled solution analyzes identity as a threat plane to protect an organization’s intellectual property, sensitive information, and deterring an attacker from an under-the-radar cyber campaign or sophisticated insider activity like IP Theft, Brand Damage, and Fraud. Gurucul provides a Hybrid Behavior Analytics (HBA) architecture with the breadth of Identity Access Intelligence to User Behavior Analytics, and the depth from cloud apps to on-premises behavior.
SEE WHAT CUSTOMERS HAVE TO SAY
Powered by Predictive Identity Based Behavior Anomaly Engine that provides:
- Largest Library of Machine Learning Algorithms
- Most Granular & Self Tuning Risk Modeling Capabilities
- Flexible Meta Data Framework
- Signature-Less Technology
- Fuzzy logic based link analysis
- Built to Scale Using Big Data Foundation
Purpose Built to Identify Behavior Anomalies
Self-training algorithms are tailored to identify learned anomalous behaviors immediately upon deploying the technology.
Context Aware Visibility of An Attack Lifecycle
Out of the box timeline view to highlight the anatomy of an advanced attack whether it be an insider or external.
Situational Awareness with 3rd Party Intelligence Feed and Threat Sharing
Gain additional context by integrating 3rd party feeds and share industry specific threat scenarios.
Detailed Insight into All Anomalous Behaviors – Endpoints, Applications, Devices, and Users
Machine learning algorithms are executed on 254 attributes to build different anomalous behavior profiles across the entities.
Advanced Visualization & Workflow Centric UI
Visually see and analyze the threat for faster incident response and customize the views based on your operational needs.
- Predict, detect, and deter insider threats & Fraud
- Proactive and actionable alerting on anomalous behaviors
- Rapid and Enhanced ROI from Defense-In-Depth Solutions (e.g. SIEM, DLP)
- Reduce the investigation time by more than 80% using contextual identity and visual investigation
- Proactively find and stop data exfiltration
- Soundproof cyber security infrastructure using Machine learning and intelligence driven big data security analytics