With enterprises rapidly adopting cloud technologies, they are facing the same security challenges with cloud applications as they did with in-house applications and systems. It is becoming increasingly difficult to control user access and activity to these systems as well as the data moved to, and maintained in these systems. While some operational and infrastructure concerns are less relevant in the cloud, issues such as data breaches, data loss, account hijacking, malicious insiders, and shared technology concerns are even more prevalent.
HOW GURUCUL CAN HELP?
Gurucul’s Cloud Analytics Platform (CAP) is an API-based CASB (Cloud Access Security Broker) built upon our core architecture PIBAE (Predictive Identity Based Behavior Anomaly Engine) to provide full insight into cloud applications with contextual views of an identity, it’s access and associated activity. This powerful approach is able to highlight behavioral anomalies, which in turn are used to identify insider threats, compromised accounts, compliance violations, data leakage and assist in investigation and forensics.
Our Big Data machine learning enabled approach along with contextual access, intelligent security analytics, and user behavior modeling can provide an organization with continuous insight into its cloud infrastructure. Cloud apps require both identity access intelligence and user behavior analytics to reduce the attack surface for accounts, unnecessary access rights and privileges, and identify, predict and prevent breaches. CAP is part of our Hybrid Behavior Analytics (HBA) architecture for on-premises and cloud using identity as a threat plane.
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
360° View of Identity, Access, and Activity
Correlate data across multiple cloud applications to create contextual identity – who is the user, what access he has, and what activity are they performing
Purpose Built to Identify Behavior Anomalies
Self-training algorithms are tailored to identify learned anomalous behaviors immediately upon deploying the technology.
Detailed Insight into all access and activity Anomalous Behaviors
Machine learning algorithms are executed on access and usage attributes to build cloud centric anomalous behavior profiles across the users.
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.
- Predict, detect and deter insider threats and cyber fraud for cloud apps via an API-based CASB solution
- Prevent data exfiltration with risk-scored time lines from predictive security analytics
- Detect high privilege account abuse, account hijacking and anomalous activity
- Real-time access analytics identify anomalies, improve access control, and data governance
- Enhance certifications with user, account, and entitlement risk determined by behavior analytics
- Reduction in accounts and access entitlements to reduce identity risk and exposure
- Leverage for hybrid deployments of on-premises and cloud behavior analytics