Architecting a Data-Centric Identity Security Infrastructure

Architecting a Data-Centric Identity Security Infrastructure 

As organizations build more interconnected digital ecosystems, securing identity is no longer just a component of cybersecurity—it is the foundation of protecting everything from data to devices. We are now seeing an unprecedented proliferation of machine identities, which frequently outnumber human identities. Yet traditional identity systems struggle to manage these effectively.  

Organizations grapple with fragmented, siloed identity data sources and IAM solutions leave blind spots and inefficiencies. The flexibility of using AI and mobile or personal devices for business operations further aggravates this issue.  

These security concerns become a critical pain point for larger enterprises that want to scale. Mergers and acquisitions complicate matters by combining disparate identity systems and policies. It frequently leads to conflicting identity data and compromised access management, posing severe security risks.  

What is the solution to making an organization’s identity security practices more effective and resilient, not just for the current threat landscape but also for next-gen risks?

The answer is to architect a data-centric identity security infrastructure, making identity data the cornerstone of all security decisions.

The Need for a Data-Centric Identity Security Infrastructure 

Traditionally, enterprises have addressed identity security problems individually, implementing separate solutions for Identity Governance and Administration (IGA), Privileged Access Management (PAM), access management, and SaaS-native systems like Microsoft Entra and Okta. Although individually functional, these tools collectively create fragmented identity data silos. As identity and application counts grow, these silos generate significant security gaps due to inconsistent data visibility and management. 

The solution lies in making identity data foundational. Identity data must be positioned at the core of every security decision, ensuring consistency, accuracy, and completeness across all processes related to authentication, authorization, and lifecycle management. 

The goal is to perfectly align with Gartner’s definition of identity-first security—an approach positioning identity-based access control as the cornerstone of cybersecurity. 

Implementing Gartner’s VIA Model 

To achieve data-centric identity security, Gartner’s VIA model (Visibility, Intelligence, Action) provides a clear and structured roadmap: 

1. Visibility: Establishing unified identity data visibility

1. Intelligence: Analyzing data for actionable insights 

1. Action: Executing real-time remediation based on intelligence

Each component is crucial for successful deployment. 

Visibility: Consolidating Fragmented Identity Data 

Organizations must first tackle fragmented identity data scattered across various sources—Active Directory, HR systems, PAM solutions, and cloud identity solutions. Consolidating these into an identity data lake is critical. This data lake must be data-agnostic, scalable, real-time, event-driven, and capable of handling vast volumes of data, both structured and unstructured. 

Once consolidated, raw identity data needs to be transformed into actionable information via a semantic layer. A semantic layer is a structured representation or model that organizes identity data into meaningful relationships and context. It turns fragmented, raw data into unified, easily understood information. 

In short, this semantic layer maps identity data into a coherent model providing unified visibility across human and non-human identities, entitlements, and actual usage. It must: 

• Ensure that diverse identity data is standardized and unified 

• Break data silos by treating access uniformly, regardless of its source 

• Leverage a graph-based structure for intuitive, multi-dimensional navigation 

• Maintain data lineage for precise traceability and remediation 

Intelligence: Identifying and Observing Anomalies 

The semantic layer significantly improves data coherence but often results in large volumes of information that are challenging to analyze manually. For this reason, the Intelligence layer’s role is crucial. It continuously observes identity data, focusing specifically on detecting: 

• Deviations 
• Discrepancies 
• Unauthorized or abnormal changes 
• Risky behavior 

Organizations benefit less from routine events than from abnormal situations requiring immediate attention. Intelligence leverages queries, usage analysis, change detection, peer group baselining, and correlation techniques.  

Observations enrich the semantic layer, enhancing decision-making in downstream systems such as PAM, IGA, and access management platforms by providing crucial context around potential risks and anomalies. 

Action: Executing Flexible Remediation 

The Action layer addresses identified issues based on intelligence. This step requires a flexible approach, capable of adapting to different scenarios. Some actions may be straightforward, such as directly writing corrections back to endpoint systems. Others require interaction with existing cybersecurity tools—IGA, PAM, or ticketing systems—emphasizing the importance of well-maintained connectors and integrations. 

Remediation often critically requires consensus from stakeholders beyond IT security teams. Engaging the business stakeholders—the first line of defense, such as line managers and resource owners—is essential to distinguish legitimate threats from false positives. This engagement transforms the security system into a collaborative “security cockpit,” amplifying the cybersecurity team’s capabilities. 

Effective collaboration requires clear roles and responsibilities across all stakeholders, ensuring that ownership and accountability are well defined when addressing identity security risks. Additionally, seamless integration with everyday digital workplace tools like Slack or Microsoft Teams, possibly enhanced by LLM-based conversational interfaces, can significantly streamline interactions, enabling quick confirmations and decisions from non-technical stakeholders. 

Strengthening Identity Security with a Data-Centric Approach 

Building a data-centric identity security infrastructure using Gartner’s VIA model provides comprehensive benefits: 

• Unified Visibility: Eliminates fragmented silos, creating a coherent identity view
• Actionable Intelligence: Proactively identifies risks and anomalies, enhancing threat detection
• Real-time Remediation: Ensures quick, precise actions tailored to diverse cybersecurity scenarios
• Collaborative Remediation: Actively involves non-technical stakeholders, significantly improving accuracy and response effectiveness

Ultimately, by placing identity data at the heart of security infrastructure, organizations significantly strengthen their security posture, achieving genuine, identity-first security. 

How RadiantOne Implements a Data-Centric Identity Security Infrastructure 

The RadiantOne platform simplifies and accelerates the transition to a data-centric identity security model. The solution consolidates identity data from legacy on-premises and cloud-based sources into a unified, standards-based, vendor-neutral identity data lake. This consolidation eliminates identity data silos and provides a global IAM data catalog with rich, attribute-enhanced user profiles. 

With RadiantOne, organizations can efficiently build unlimited virtual views of identity data that are unified across various protocols (LDAP, SQL, REST, SCIM, Web Service APIs). Its low-code/no-code transformation logic enables seamless data mapping, ensuring quick adaptability to changing business and security requirements without disrupting existing systems. 

RadiantOne scales to support hundreds of millions of identities, adding resilience and speed through a highly available, near real-time identity service. The solution automates identity data management, streamlines user and group management, rationalizes group memberships, and dynamically controls access rights. 

Its visibility capability provides a real-time, unified view of the situation for all human and non-human identities down to a permission level. Coupled with its observability capabilities, it spots misconfiguration and detects anomalies or abnormal changes to keep the identity landscape under control. 

Most notably, the platform’s AI-powered assistant, AIDA, simplifies user access reviews, swiftly identifying anomalies and providing actionable remediation suggestions. By automating tedious manual reviews, AIDA drastically reduces administrative effort and improves decision accuracy, making it easier to enforce a least-privilege approach and continuous compliance.