A major cause 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 privileged 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’s Access Analytics Platform (AAP) – Features
The Gurucul Access Analytics Platform 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).
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.
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 ongoing governance process.
Enables real-time risk-based access policy enforcement of multi-factor authentication for internal users and customer identity and access management (CIAM), using risk scores backed by machine learning and behavior analytics on big data. Successfully deployed by Fortune 50 company for their 8 million consumers.
Enables automated workflow approvals with dynamically generated risk scores by analyzing peer groups, entitlement combinations and application classification in real-time. Using AAP’s award-winning machine learning algorithms, customers reported a 65% reduction in on-boarding time using Gurucul’s risk-based dynamic provisioning.
Discovers, risk ranks and monitors accounts with privileged access. Identify outlier access and anomalous behavior with advanced machine learning. Backdoor access and its misuse will be a thing of the past.
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 role-based access control (RBAC). 58% reduction in business time to review new roles and sign off.
Offers a contextual identity and access management (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 exporting results for reporting.
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)
Gurucul Access Analytics Successes
Gurucul reduced the number of accounts and entitlements by 83% for a financial firm, plus defined intelligent roles and provided dynamic access provisioning, using a behavior-based risk context.
Gurucul often finds high privileged access abuse and anomalous behavior in unexpected areas as unknown unknowns.
Gurucul discovered terminated accounts with access to cloud applications.