Access Analytics Platform (AAP)

Gurucul Access Analytics

• On average 50% of privileged entitlements are unknown and outside the vault.
• Radical reduction excess access in your environment.
• 60% reduction in manager time during certifications.
• Are terminated and orphaned accounts being misused?

A root of modern threat involves compromise or misuse of identities. Users have multiple accounts and entitlements, often in excess, providing an opportunistic environment for cyber crime, insiders and advanced attacks. A CIO’s goal is widespread data access and enablement, while CISOs struggle with declarative defenses and controls. The outcome is data breaches and escalating costs as preventive defenses decline in effectiveness. The rapidly growing volume of security data needs data science.

Why Choose Gurucul Access Analytics?

Real-time 360° contextual view of identities, access and activities.

Identity analytics and roles from behavior analytics machine learning.

Radical reduction of accounts and access entitlements using behavior-based access.

High privilege access detection, plus obsolete, orphan and unused access reporting.

Risk based certifications and dynamic access provisioning reduces effort and errors.

Access outliers based on usage and dynamic peer group analytics.


Gurucul Access Analytics Features

Gurucul Access Analytics has three components to address threat, access and cloud use, uniquely combining data science for user and entity behavior analytics (UEBA) and identity analytics (IdA)

Risk-Based
Certifications

Reduces rubber-stamping by providing decision makers with risk, access usage and peer group analytics. This can be done seamlessly with your existing access attestation tool or using Gurucul Access Analytics’ mobile enabled certifications.

Outlier Analysis
Workbench

Provides a user-friendly interface to analyze outlier access with Gurucul’s award-winning machine learning algorithms. Gurucul STUDIO™ enables custom model development without coding and with minimal data science skills. Companies initially reduce access by over 40% and maintain these analytics as part of their on-going governance process.

Risk-Based Adaptive
Authentication

Enables real-time risk-based access policy enforcement of multi-factor authentication for internal users and customers (CIAM) using risk scores backed by machine learning and behavior analytics on big data platform. Successfully deployed for 8 million customers at a Fortune 50 company.

Dynamic
Provisioning

Enables automated workflow approvals with dynamically generated risk scores by analyzing peer groups, entitlement combinations and application classification in real-time using Gurucul’s award winning machine learning algorithms. Customers reported a 65% reduction in on-boarding time using Gurucul’s risk-based dynamic provisioning.

Privileged Access
Intelligence

Discover, risk rank and monitor accounts with privileged access.  Identify outlier access and anomalous behavior with Gurucul machine learning. Backdoor access and its misuse will be a thing of the past.

Intelligent Roles

Provides role mining, role consolidation, and role comparison using machine learning algorithms and usage data context. Avoid garbage-in-garbage-out of over-provisioned rubber-stamped access entitlements. Business user, application and attribute RBAC. 58% reduction in business time to review new roles and sign off.

Gurucul Miner™

Offers a contextual IAM search using big data to mine linked users, accounts, entitlements,
structured and unstructured data, along with risk score and peer group analytics, which include the capability of saving and and exporting results for reporting.

Reports

Delivers 100+ Identity Analytics reports available out of the box, with the capability to customize, schedule and automate reports.

What makes Gurucul Access Analytics more effective?

Gurucul Access Analytics’ core architecture is built on PIBAE™ (Predictive Identity-based Behavior Anomaly Engine)

Largest library of machine learning algorithms

Dynamic peer groups improve clustering and outlier machine learning accuracy

Awareness of time-based norms such as accepted workflows and operational changes

Built for scale with open choice big data

Most granular & self tuning risk modeling capabilities

Out of the box algorithms learn anomalous behaviors immediately upon deployment

PIBAE

Gurucul Access Analytics Successes

Gurucul Access Analytics


SC Mag Award US
SC Mag Award Europe

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