How Your Organization Can Eliminate Entitlement Creep

The Growth of Artificial Intelligence in Identity Governance

Organizations are facing increasing pressure to provide employees and contractors with the right access to the right applications and systems at the right time. But how can they do this with their existing, manually-driven Identity Governance and Administration (IGA) solutions and processes? How can security and IT professionals address the needs of the new remote workforce and its demands for access to new cloud applications and services? Combined with new machine identity types, accelerated DevOps/Agile development methodologies, and unplanned organizational changes, static IGA solutions and processes need to become more flexible, more dynamic, and more automated. 

With the introduction of artificial intelligence (AI) and machine learning (ML) into IGA, organizations have a clear path to hyper-automating their existing identity governance solution and processes. By applying AI and ML, enterprises can further streamline and automate intelligence across all identity governance use cases, including access requests and approvals, access reviews, and role engineering. Here are a few examples of how AI and ML can hyper-automate IGA solutions and processes to help combat your organization’s entitlement creep problems: 

  • Identify access risks across the entire organization and provide actionable insights to help accelerate the removal of overprivileged access
  • Identify excessive privileges, orphaned accounts, and provide confidence scoring (example: low, medium, and high) in order to provide the right level of security risk context 
  • Enable micro-certifications, where only a small set of entitlements and roles are approved between annual or biannual certification campaigns

While no new technology is 100% foolproof, the introduction of AI and ML capabilities into identity governance solutions and processes provides organizations with the most promising way to address the silent access challenge known as entitlement creep.

ForgeRock’s Modern Approach: Autonomous Identity  

ForgeRock Autonomous Identity provides real-time, continuous enterprise-wide user access visibility. The solution allows organizations to accelerate secure workforce access, achieve regulatory compliance, mitigate risks, and reduce costs. By leveraging AI and  ML techniques, Autonomous Identity collects and analyzes all identity data to identify security access and risk blind spots. The solution provides organizations with a complete user access landscape viewwhat good and bad access looks like across the entire enterprise. It provides organizations with wider and deeper insight into the risks associated with user access by providing enterprise-wide contextual insights, high-risk user access awareness, and remediation recommendations, such as the removal of overprivileged access, excessive permissions, and orphaned accounts. 

How it Works

ForgeRock Autonomous Identity links users to entitlements at the lowest attribute level. The solution uses profile data to determine the likelihood that an individual will need an entitlement, based on how entitlements are currently distributed across the organization. By applying AI and ML techniques, Autonomous Identity can quickly analyze all your organization’s identity data and identify overprivileged access, excessive permissions, and orphaned accounts. All are key contributors to your organization’s entitlement creep challenges. 

ForgeRock Autonomous Identity - How It Works.png

Why ForgeRock Autonomous Identity?

Here’s how Autonomous Identity’s unique and highly differentiated capabilities address entitlement creep: 

  • Global Visibility: By leveraging AI-driven identity analytics, you can collect and analyze identity data (example: accounts, roles, assignments, entitlements, and more) from diverse identity, governance, and infrastructure data sources in order to provide enterprise-wide visibility to all identities and what they have access to, including over privileged user access. This approach provides your security and risk teams with contextual insights into low-, medium-, and high-risk user access at scale.
  • Data Agnostic: ForgeRock Autonomous Identity works with all identity data types to develop a complete view of the user access landscape. By consuming and analyzing tens of millions of data points quickly, Autonomous Identity can predict and recommend user access rights and highlight potential risks. Total landscape visibility provides highly accurate models based on what good access should and shouldn’t look like, including excessive permissions. Unlike other “black box” identity analytics solutions that are based on static rules, roles, and peer group analysis, Autonomous Identity relies strictly on organizational data to develop an analysis that is free from bias originating from human-derived rules and roles that exist in your existing identity governance solution.
  • Transparent AI: Unlike other “black box” identity analytics solutions, ForgeRock Autonomous Identity allows you to fully comprehend how and why risk confidence scores are determined. By visually presenting low-, medium-, and high-risk confidence scores together, security and risk professionals can contextually understand what key risk indicators were met and, more importantly, why they were met. For example, why are certain employee and contractor accounts orphaned? This AI-driven approach recommends risk-based identity governance remediation updates based on enterprise-wide confidence scores.

Eliminate Entitlement Creep with AI-Driven Identity Analytics

In today’s new reality, organizations have dynamic business challenges. They need a dynamic solution to help them achieve their business goals and grow the business. By applying AI-driven identity analytics, organizations can hyper-automate their existing identity governance solutions and processes, thereby eliminating entitlement creep. By detecting user access patternsidentity analytics can quickly highlight inappropriate user access. In turn, AI-driven identity analytics can automate the removal of high-confidence and low-risk access rights, lowering the risk of entitlement creep across your organization. 

To learn more about ForgeRock Autonomous Identity, read the new KuppingerCole white paper “Overcoming Identity Governance Challenges with ForgeRock Autonomous Identity.”

*** This is a Security Bloggers Network syndicated blog from Forgerock Blog authored by Tim Bedard. Read the original post at: https://www.forgerock.com/blog/how-your-organization-can-eliminate-entitlement-creep