Redefining Identity: ForgeRock Autonomous Identity
IT and Security teams are experiencing identity governance fatigue because they are exhausted from manually reviewing and approving access requests and rubber-stamping certifications. To address this weariness, ForgeRock is providing a new modern approach to identity. ForgeRock Autonomous Identity is an artificial intelligence (AI)-driven identity analytics solution, that allows you to overcome identity governance fatigue.
ForgeRock Autonomous Identity provides real-time, continuous enterprise-wide user access visibility, control, and remediation. By leveraging AI and machine learning techniques, Autonomous Identity collects and analyzes all identity data—such as accounts, roles, assignments, user activity, and entitlements—to identify security access and risk blind spots.
The solution provides you 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. Autonomous Identity can be overlaid onto legacy IGA solutions, enabling your organization to increase operational efficiencies, accelerate decision making and maximize existing identity investments.
Leverage Your Existing Identity Investments
ForgeRock Autonomous Identity works with your existing identity infrastructure to develop a complete view of the user access landscape. This includes identity management, Microsoft Active Directory, identity governance, databases, LDAP systems, and other identity data sources in your organization. The landscape provides highly accurate models, showing what good access should and shouldn’t look like.
Unlike legacy IGA solutions that are based on leveraging static rules, roles, and peer group analysis, Autonomous Identity relies strictly on the data in your organization to develop an analysis that is free from any bias coming from human-derived rules and roles that exist in your identity management or identity governance solution.
How It Works
Autonomous Identity links users to entitlements at the lowest attribute level. The solution uses profile data to determine the likelihood an individual will need an entitlement, based on how entitlements are currently distributed across the organization.
Why ForgeRock Autonomous Identity?
Autonomous Identity addresses identity governance fatigue with unique and highly differentiated capabilities, including:
- Global visibility: By leveraging AI-driven identity analytics, you can collect and analyze identity data (examples: accounts, roles, user activity, entitlements, and more) from diverse identity, governance, and infrastructure solutions in order to provide enterprise-wide visibility of all identities and what they have access to across the entire enterprise. This approach provides your security and risk teams with contextual insights into low-, medium-, and high-risk user access at scale.
- Highly scalable: As new identity data is collected and old data is purged, the AI and machine learning model evolves and learns the dynamic changes within the enterprise. By leveraging predefined machine learning techniques and algorithms, you can quickly predict, recommend, and identify outliers. This intelligence-based approach allows your security and risk professionals to automatically analyze and model high volumes of identity data to identify high-risk user access and unauthorized or unknown user access across the entire organization.
- Data driven: With Autonomous Identity, you can contextually examine all identity-related data and identify and recommend the right level of user access rights. This approach provides the ability to identify and apply appropriate birthright or leaver user access rights to accounts, applications, systems, roles, entitlements, and more. This process reduces the overall request volume by predicting appropriate user access at the right time to the right resources.
- Transparent AI: Unlike “black box” identity analytics solutions, 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, your security and risk professionals can contextually understand which key risk indicators were met. This AI-driven approach recommends risk-based identity and governance remediation updates based on enterprise-wide confidence scores.
- Dynamic analysis: With intelligent data stream processing, you can leverage existing and diverse identity, governance, and infrastructure data sources to continuously collect and process high-velocity, high-volume data (examples: roles, entitlements, attributes assignments, and more) from across the enterprise. Combined with a highly scalable and distributed microservices architecture, enterprises can process and analyze tens of millions of data points quickly to predict and recommend user access rights and highlight potential risks. This intelligence-based approach enables security and risk professionals to accelerate their decision-making process.
Autonomous Identity provides you the unprecedented ability to reduce costs while simultaneously lowering risks across your organization. It is a game-changing solution that is redefining identity by providing organizations with the following key business benefits:
To learn more about ForgeRock Autonomous Identity, watch the “Identity Redefined: Eliminate Risks and Cut Costs with AI-Powered Identity Analytics” webinar with ForgeRock and Accenture.
*** 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/autonomous-identity-how-overcome-identity-governance-fatigue